VictorJuiz/thesis huggingface dataset:
Landscapes of Locura: The Creative Possibilities of Queer Afro-Dominican Gender Performance in Digital Media
Keywords: Dominican Republic
Afro-Caribbean
Feminism
Queer theory
Gender identity
African diaspora in art
Black people
Caribbean Area
Text
Thesis

"Landscapes of Locura: The Creative Possibilities of Queer Afro-Dominican Gender Performance in Digital Media" dives into the intricacies of queer Afro-Dominican gender performance and its effects on black insurgency in the Dominican Republic through digital performance and creative world-building practices. Here, “queer Afro-Dominican” refers to black and afro-descendent Dominicans who actively queer notions of race, gender, and sexuality through radical performance and embodiments of the fluid identities they hold. With research grounded with a focus on the materiality of queer Afro-Dominicanidad through an analysis of gender performance from three feminine Afro-Dominican musical artists: Tokischa, Gailen La Moyeta, and La Pajarita La Paul, this paper explores themes relating to queer Afro-Dominican liberatory tactics rooted in performance. These three artists and their performance of gendered lyric, imagery, and aesthetics provide a case study for the ways in which embodied identities, desire and intimacy, and performance as autonomy act as entry points into discussions of queer Afro-Dominicanidad and the liberatory possibilities of queer black subjectivities in the Dominican Republic. This is a trek into the uncharted waters of non-normative femininities, imaginative decolonial work, and the demonic grounds where queer Afro-Dominican create spaces of temporal freedoms. Additionally, there is reflection on Landscapes of Locura, an installation that acts as a framework of observing, understanding, and assessing these queer Afro-Dominican performances of gender, is discussed. This use of installation art taps into the world-making practices of queer Afro-Dominicans by creating a physical landscape informed by such practices of freedom, and thus allows for another mode of analysis of queer Afro-Dominicanidad and its performances of gender.
Language, culture, and systems of evaluation : computational analyses of college admissions essays
Keywords: Education.

Each year, high school students from all social strata apply to selective colleges and universities. One well known element to the application process for these schools is the solicitation of personal statements where applicants describe themselves, their interests, their communities, and other information they deem relevant to their college application. Other features of the same applications, specifically standardized test scores, have been consistent sources of controversy for decades given their strong correlations with social class (approximated by household income). This dissertation expands the literature on evaluation, culture, language, and college admissions by shifting the analytical lens onto admissions essays and leveraging tools from computational text analysis. Chapter two does this bluntly: using computationally derived features of admissions essays as predictors, we find that admissions essays are stronger predictors of income than SAT scores but also that the features are very strong predictors of SAT scores. Chapter three considers how students might see applying to college as a time to demonstrate multilingual competence, specifically Spanish, despite long histories of prejudice in K-12 education. And finally, chapter four shows how admissions essays written by transfer applicants are patterned by specific academic pathways (community college students vs. applicants enrolled in four year schools) but also how essay prompts might reduce or exacerbate these differences. Combined, this dissertation provides important clarifications for data science in education as well as the growing interest of computational methods in social science
A laser-driven fiber-optic gyroscope suitable for inertial guidance of transoceanic flights
Keywords: Electrical Engineering.

The performance of commercially available fiber optic gyroscopes (FOGs) is limited by their scale-factor instability and noise, which are both due to high noise and poor wavelength stability of the superfluorescent fiber source (SFS) used to interrogate the FOG's sensing coil. A promising way forward is to replace the SFS with a laser, which has a much lower noise and better wavelength stability. Historically, lasers have not been used in FOGs because their high temporal coherence introduces several dominant sources of noise and drift in the fiber coil. However, recent investigations have shown that laser-driven FOGs can have exceedingly low noise and good scale-factor stability if the coherence of the laser is suppressed by broadening the laser linewidth with external phase modulation. In this thesis, we develop a new analytical model that derives the error in an aircraft's position from a gyroscope's known noise and drift, inferred from a measured Allan deviation of the sensor's output time trace. Using this model, we derive the noise and drift required to satisfy the Federal Aviation Administration's requirements for a trans-Pacific flight. We also developed a complete model of the coherence of a laser broadened by wideband phase modulation and use this model to optimize the coherence suppression. With most of the coherent effects suppressed by an optimally modulated laser, we performed one of the most exhaustive studies on the sources of drift conducted on a laser-driven FOG. In the process, we identified four dominant sources of drift, and implemented a variety of suppression techniques to reduce them. As a result, the long-term stability of the 3-km FOG tested in this research was improved by a factor of 30 relative to the previous world-record laser-driven FOG. This FOG exhibited a noise of 0.9 mdeg/√hour and a record-breaking drift of 12.7 mdeg/hour (characterized using the Allan-deviation maximum). The measured output of this FOG was used to simulate 20 10-hour trans-Pacific flights of an aircraft guided solely by inertial sensors. 95% of the flights landed within ±10 nmi of their intended destination. To our knowledge, this is the first report of a laser-driven FOG that meets the Federal Aviation Administration's criterion for aircraft navigation
Learning and incentives in waitlist mechanisms
Keywords: Management Science and Engineering.

This dissertation is motivated by the deceased donor kidney allocation system in the United States. Through stylized models, I develop theories to examine the interplay of learning and incentives in such allocation markets. In Chapter 1, I consider a mechanism design problem where a social planner needs to decide whether and how to allocate a single object to a queue of strategic and privately informed agents. Using tools from operations research and voting literatures, I propose a simple mechanism that can effectively crowdsource agents' private information by balancing their strategic incentives and planner's learning goal. In Chapter 2, I add inter-temporal dynamics to study the equilibrium and optimal strategy in the presence of both dynamic incentives and observational learning in first-come-first-served waitlists. On the one hand, the availability of object implies preceding agents' remaining on the waitlist, which incentivizes agents to accept. On the other hand, it may also imply negative object quality via observational learning, incentivizing agents to reject. I show how these opposing forces come into play. Finally, in Chapter 3 I develop machine learning models to predict hard-to-place kidneys based on donor characteristics and signals from waitlist candidates
Learning in the forest : an exploration of Waorani education and its interaction with formal state schooling in the Ecuadorian Amazon
Keywords: Anthropology.

In this dissertation I seek to build upon global research examining differences between formal education and local learning systems in minority cultures like Indigenous Nations, Amazonian research focused on drivers of cultural change, and past anthropological research describing Waorani pedagogy and the impacts of formal State education. Across three chapters, I explore the Waorani system of learning by examining how they organize information, how they learn in and navigate through a landscape infused by magic and constrained by threats of danger, and how, where and when they learn on days with and without school. I explore Waorani mental concepts or "schema", epistemology, and the timing and spatial distribution of local and school learning experiences, while simultaneously contributing to anthropological literature more broadly by calling into question assumptions about the inefficacy of hunter-gatherer classification systems and the everyday vulnerability of perspective taking in Amazonian societies. Finally, I suggest that timing could be an essential element to consider when examining access to local learning contexts and seeking to help youth develop successful multicultural identities according to local objectives
Learning Multimodal Rewards from Rankings
Keywords: Computer Science
HRI, reward learning, multi-modality, rankings, active learning
Text
Thesis

Learning from human feedback has been shown to be a useful approach in acquiring robot reward functions. However, expert feedback is often assumed to be drawn from an underlying unimodal reward function. This assumption does not always hold, including in settings where multiple experts provide data or when a single expert provides data for different tasks. We thus have to go beyond learning a unimodal reward and focus on learning a multimodal reward function. We formulate the multimodal reward learning as a mixture learning problem and develop a novel ranking-based learning approach, in which the experts are only required to rank a given set of trajectories. Furthermore, as access to interaction data is often expensive in robotics, we develop an active querying approach to accelerate the learning process. We conduct experiments and user studies using a multi-task variant of OpenAI's LunarLander and a real Fetch robot, where we collect data from multiple users with different preferences. The results suggest that our approach can efficiently learn multimodal reward functions, and improve data-efficiency over benchmark methods that we adapt to our learning problem.
Learning Object-Centric Visual Representations for Common Sense Reasoning
Keywords: Machine learning
computer vision
cognitive science
Text
Thesis

People understand the world as a sum of its parts. Our effortless mental ability to simulate and imagine what will happen crucially depends on a scene representation that is compositional with respect to objects and the interactions between them. Similarly, learning representations with an emphasis on the perception and understanding of objects plays a key role in building human-like AI capable of supporting higher-level cognitive abilities such as common sense reasoning, causal reasoning, and goal-oriented planning. Many current methods in machine learning focus on learning structured representations in which objects are only implicitly represented, which poses a threat to model interpretability. Motivated by these observations, this work aims to develop algorithms for learning object-centric representations in which objects are explicitly represented. Given the importance of objects in human cognition, we draw inspiration from cognitive science to motivate and provide theoretical underpinnings. Specifically, we take a rationalist approach in augmenting deep neural network architectures to exhibit object-centric representations, and demonstrate empirically how these representations can be efficieintly leveraged for downstream tasks such as controllable image synthesis.
Learning preferences for interactive autonomy
Keywords: Electrical Engineering.

When robots enter everyday human environments, they need to understand their tasks and how they should perform those tasks. To encode these, reward functions, which specify the objective of a robot, are employed. However, designing reward functions can be extremely challenging for complex tasks and environments. A more promising approach is to learn reward functions from humans. Recently, several robot learning works embrace this approach and leverage human demonstrations to learn the reward functions. Known as inverse reinforcement learning, this approach relies on a fundamental assumption: humans can provide near-optimal demonstrations to the robot. Unfortunately, this is rarely the case: human demonstrations are often suboptimal due to various reasons, e.g., difficulty of teleoperation, robot having high degrees of freedom, or humans' cognitive limitations. This thesis is an attempt towards learning reward functions from humans by using other more reliable data modalities. Specifically, we study how reward functions can be learned using comparative feedback, in which the human user compares multiple robot trajectories instead of (or in addition to) providing demonstrations. To this end, we first propose various forms of comparative feedback, e.g., pairwise comparisons, best-of-many choices, rankings, scaled comparisons; and describe how a robot can use these various forms of human feedback to infer a reward function, which may be parametric or non-parametric. We discuss the pros and cons of each comparative feedback modality in detail, and show how such feedback enables us to outperform standard inverse reinforcement learning that only utilizes demonstrations. To increase data-efficiency, we also propose active learning techniques to enable the robot to ask for comparison feedback that optimizes for the expected information that will be gained from that user feedback
Leaving Brussels for Moscow: Examining External Factors in Yerevan’s Decision to Forgo the 2013 EU-Armenia Association Agreement
Keywords: Eurasian Union
EAEU
Eurasian Economic Union
Eastern Partnership
Armenia
European Union
South Caucasus
Text
Thesis

On September 3rd 2013, President Serzh Sargsyan announced that Armenia would abandon its proposed Association Agreement with the European Union after years of negotiations. In place of this agreement, Armenia would pursue full membership in the Russian-led Eurasian Economic Union (EAEU). Although this abrupt decision came as a surprise to Armenian political actors and many western observers, this development was the product of years of political maneuvering by Moscow towards Armenia as part of the creation of an alternative model of regional integration within the former Soviet Union. Considering that the European Union and Russia held relative parity with one another as trading partners of Armenia and both Brussels and Moscow held close diplomatic ties with Yerevan this begs the question: what specifically allowed Russia to pry Armenia away from its path of European Integration and secure Yerevan’s membership in the EAEU? In exploring Sargsyan’s decision, this paper will investigate the elements differentiating Russia and Europe’s trading relationship with Armenia, differences between Brussels’ and Moscow’s ability to act as an energy provider to Armenia, and Moscow’s role as a guarantor of security to Yerevan.
Legacy Media Coverage of Russia’s Activities in the Arctic
Keywords: Arctic Regions
Geopolitics
Russia
Militarization
Journalists
Press coverage
Reporters and reporting
Mass media > Political aspects
Climatic changes > Government policy
Climatic changes > Political aspects
Text
Capstone
Thesis
Student project report

The changing conditions in the Arctic have sparked interest for stakeholders across the globe. The melting ice sheets create both opportunities and challenges. New transport routes are opening up that would shorten delivery times to both Europe and Asia significantly. Oil and gas exploration is of interest to many. Warmer temperatures threaten biodiversity and the communities dependent thereupon. Geopolitical and security issues are of concern and actors such as China and the EU are vying for position. With the largest Arctic coastline of all the Arctic states, Russia has by far the most dominating presence in the region.
For decades, Russia’s motivations, both generally and in the Arctic, have been an enigma for Western audiences to decipher, which leaves room for various interpretations and the potential for misunderstanding. The media plays a significant role when it comes to informing the public by drawing insights from current developments. The media has the power to shape and influence the public’s opinion, whether rightly or wrongly.
This study incorporates a content analysis of legacy news media outlets from a multi-national perspective. Key themes and narratives from the US, Germany, Norway and Iceland are evaluated and compared as these states all have a claim in the Arctic and yet have a unique relationship with Russia.
From a multi-national perspective, the media coverage in this study has revealed the Arctic’s distinctive duality of cooperation and tension. The coverage, as expected, reflects the differing national stances towards Russia whereby the distinctive interests of each state are seen in the reporting. These discrepancies are indicative of the respective government’s commitment to and policy in the region in the future. As we have witnessed in the wake of Russia’s invasion into Ukraine, each state’s relationship with Russia and the subsequent reporting of relations can and will change in accordance with world events. Such changes in dynamics provide ample material for a future study.
Lesen und erleben : Zugänge zum heiligen land in deutschsprachigen pilgertexten des 15. jahrhunderts
Keywords: German Studies.

In the late medieval German speaking lands, texts, objects, and images that sought to make the spatially distant Holy Land and the temporally distant Biblical events present were widespread. To these media belonged late medieval pilgrimage texts, which often incorporated images, offered modes of reception that allowed to imaginatively approach the spatially distant Holy Land as well as the temporally distant events of salvation history that took place there without going on a journey to the Levante. In my dissertation, I closely analyze three 15th century pilgrimage texts written in the German vernacular: Felix Fabri's Die Sionpilger, Hans Tucher's Reise ins Gelobte Land and Arnold of Harff's Die Pilgerfahrt des Ritters Arnold von Harff. Late medieval pilgrimage texts, I argue in the dissertation, aim at a wide spectrum of reader response. They invite their readers to recreate, share and understand the shared and lived experiences of late medieval pilgrimages to Jerusalem from afar. To this end, they develop a set of literary, medial and material strategies. As I show in the four chapters of my dissertation, pilgrimage texts allow for different degrees of involvement and participation in the narrated experiences of travelling to the Holy Land. In some cases, the audience is confined to the role of a passive observer who can gain an abstract understanding of pilgrimage by reading. Other modes allow for an active participation from afar or even evoke imaginary lived experiences of pilgrimage. I show that late medieval German pilgrimage texts do far more than just giving accounts of completed pilgrimages. I propose to rather understand pilgrimage accounts as texts which cater to the wishes of their readership to experience the faraway places of salvation -- even if only by means of reading. In so doing, these texts offer to their readers options to build experiences of pilgrimage without travelling. Even though their contemporary readers might have never set foot in the Holy Land, they thus could still engage with the loca sancta and hope for their salvific effects by engaging with words, images, and objects
Leveraging near-term quantum computing for spin chemistry and combinatorial optimization
Keywords: Electrical Engineering.

Quantum computing offers computational tools and speed-ups beyond the reach of classical computers in the long run, yet demonstrating the computational advantage of small-scale near-term quantum devices remains a challenge today. In this thesis, I introduce two applications of near-term quantum computers from the fields of spin chemistry and combinatorial optimization. In the first part of my thesis, I discuss the quantum beats phenomena that occur in spin chemistry when geminate radical pairs go through singlet-to-triplet conversions under hyperfine coupling interactions and an external magnetic field. I demonstrate that both the coherent time evolution and the thermal relaxation of these radical pair systems can be efficiently simulated on a quantum computer, both hardware and simulator. I introduce the first Hamiltonian simulation method on a quantum computer that can simulate the quantum beats phenomenon for radical pair systems with nontrivial hyperfine interactions under an arbitrary magnetic field, by utilizing Hamiltonian partitioning strategies. The second part of my thesis focuses on the open-pit mining problem, where the optimal mine digging pattern that maximizes the profit is searched for, while obeying slope constraints. This optimization is traditionally solved as a maximum closure problem. Our algorithm formulates this task as a Hamiltonian ground state search in order to map it to a quantum computer, and utilizes VQE as a subroutine to find the optimal solution. I show that the Hamiltonian can be decomposed into smaller, classically correlated partitions that can each be iteratively optimized. This will allow us to make use of near-term quantum hardware for larger scale optimization problems