VictorJuiz/thesis huggingface dataset:
Cloud-Edge Hybrid Robotic Systems for Physical Human Robot Interactions

Cloud Robotics is a new paradigm where distributed robots are connected to cloud services via networks to access “unlimited” computation power. Combined with advanced network technology, such as 5G and Wi-Fi 6, it can support service robots operating under unstructured, human rich environments on a global scale. Cloud Robotics has scalable servers that host artificial intelligence, robotic vision, crowd-sourcing, and web-based human computer interface (HCI). These modular Cloud Robotic infrastructures enable control and monitoring of distributed service robots that require sophisticated physical human robot interactions (pHRIs) and human guided tele-operations./nCloud Robotics is also capable of scale up and down robotic service deployments based on rapid changes in user demands. A similar feature in Cloud-based video conferencing services has shown great value in scaling up and down based on user demands during the on-going Covid-19 pandemic. The ability to match user demands will be an important advantage of using Cloud Robotics to keep the operational cost down for service robots applications, where mixed Cloud Robotic modules can be selected for different environments on demand./nBesides above advantages, Cloud Robotic systems pay the additional price of network communication. There are three major network communication costs that hinder effective deployment of cloud robotics: (1) network bandwidth, (2) privacy and security, (3) network latency and variability. With the emerging high speed 5G and Wi-Fi 6 technology, the cost of network speed and bandwidth are dropping significantly, hence the value of Cloud Robotic services will eventually triumph the cost of network communication. However, if we want to use Cloud Robotic services to control dynamic, compliant, service robots with feedbacks, unpredictable variable delays caused by network routine protocols over long physical distances presents a major obstacle./nIn this thesis, we propose a Cloud-Edge hybrid robotic system to enable dynamic, compliant, feedback controls for physical human robot interactions (pHRIs). Specifically, we built a framework to (1) move centralized high-level controllers and computational intensive perception services to the Cloud; (2) deploy low latency, agile, Edge Robotic controller to handle dynamic and compliant motions; (3) implement a hybrid, two-level feedback controller leveraging both the Cloud and the Edge; (4) use robotic-learning algorithms to perform motion segmentation and synthesis to mitigate network latencies within the Cloud-Edge perception feedback loop. We demonstrate the robustness of the above framework using different robots, including a dual arm robot (Yumi) from ABB, a dynamic self-balancing robot (Igor) and a compliant 5 degree-of-freedom (DoF) robot arm both from Hebi Robotics, and a humanoid robot (Pepper) from Softbank Robotics. A copy of the dissertation talk including video demonstrations can be found here: https://drive.google.com/drive/folders/1rh8gCydsXCpGJCI6n31mwgTdsJdjJfn-?usp=sharing

Advisor: Sojoudi, Somayeh
New Frontiers for Physics Beyond the Standard Model

We present three distinct pathways for theory and experiment beyond the Standard Model. First, we propose an experimental design of a laboratory search for axions based on photon regeneration with superconducting RF cavities. We then study a novel production mechanism for ultralight vector dark matter in the early universe based on a parametric resonance instability. Finally, we show that white dwarfs are in fact ideal detectors of ultra-heavy DM over large regions of parameter space.

Advisor: Hall, Lawrence J
Rajendran, Surjeet
The Geometry of Divisors on Matroids

Matroids are combinatorial abstractions of hyperplane arrangements, and have been a bridge for fruitful interactions between combinatorics and algebraic geometry. In particular, the recent development of the Hodge theory of matroids in [AHK18] showed that the Chow ring of a matroid satisfies properties enjoyed by cohomology rings of smooth complex projective varieties. Namely, these are the Poincare duality property, the hard Lefschetz property, and the Hodge-Riemann relations. The validity of these properties resolved several major conjectures in matroid theory./nIn this thesis, we introduce a presentation of the Chow ring of a matroid by a new set of generators, called "simplicial generators." These generators are analogous to nef divisors on projective toric varieties, and admit a combinatorial interpretation via the theory of matroid quotients. Using this combinatorial interpretation, we (i) produce a bijection between a monomial basis of the Chow ring and a relative generalization of Schubert matroids, (ii) recover the Poincare duality property, (iii) give a formula for the volume polynomial, which we show is log-concave in the positive orthant, and (iv) recover the validity of Hodge-Riemann relations in degree 1, which is the part of the Hodge theory of matroids that currently accounts for all combinatorial applications of [AHK18]. Our work avoids the use of "flips," which is the key technical tool employed in [AHK18]. We also apply the tools developed here to study two particular divisor classes motivated by the geometry of wonderful compactifications of hyperplane arrangement complements.

Advisor: Eisenbud, David
Quantifying Links Between Fire and Water Cycles Across Time, Place and Processes, in California's Sierra Nevada

Drought, elevated temperatures, and extended fire seasons combine with high fuel loads to increase the scale and severity of wildfires in California. Many of these fires occur in the forested montane watersheds that provide approximately 60% of the developed water supply of the state, creating a critical nexus between water and fire from a management perspective. However, the links between hydrological and fire processes go well beyond a common dependence on forests. Both water and fire cycles are impacted by, and impact upon the growth, spread, function, and disturbance of vegetation communities. This means there are multiple processes linking plants, fire and water. With climate change projected to warm temperatures, reduce snowpack, extend fire seasons, and increase drought stress on Californian watersheds, foresters are turning to alternative forest management strategies. One such strategy involves the re-introduction of frequent mixed-severity fire into the landscape to lower fuel loads and reduce the risk of catastrophic fires. Co-benefits of this strategy are anticipated to include greater water yields and storage, and increased landscape diversity and forest resilience. In my primary study site of the Illilouette Creek Basin (in Yosemite National Park, California), this strategy has proven to be successful to date. Many important knowledge gaps remain, however, including how the strategy of re-introduce fire will impact the water cycle as climates warm, how transferable this strategy is to other basin, the potential implications of frequent burning on erosion and water quality, and how changes in water storage in fire-treated landscapes, and specifically in soil moisture, might modify the resulting fire regime. To answer these questions, this dissertation draws on satellite and field collected data, laboratory experiments, and hydrological and statistical modeling to explore fire-vegetation-water-climate feedbacks and inform future forest management in California.

Advisor: Thompson, Sally E
Memorials and the Cult of Apology

Memorials and the Cult of Apology examines how contemporary memorials have come to embody more than memory. It begins with a simple observation of the growing demand for apologies across the globe and the related proliferation of memorials that aim to atone for past injustices. In effect, apologies are being materialized into memorials, a phenomenon of global importance, which presents a major shift in national self-representation. In the broadest terms, my research is an intervention into the cultural history of the built environment. As the first scholarly work to address memorials as apologies, my dissertation builds an empirical and theoretical understanding of multiple aspects of apology and memorialization, of their material forms, the actors involved, and the diverse effects built apologies produce. It uses five representative case studies located in Berlin, Buenos Aires, and San Francisco, to develop this argument. Since memorialization is an inherently interdisciplinary topic, my work incorporates methods, readings, and theories from a vast array of humanistic disciplines, particularly postcolonial theory, Holocaust and human rights scholarship, and debates about justice, recognition, reparation, and morality. My archival and field research combines methods drawn from architectural history and the humanities ¬–close reading, literary interpretation, and storytelling–, which I apply to the formal analysis of built memorials and their urban contexts. This formal analysis is complemented with ethnographic interviews with designers, experts and site visitors, as well as participant observation of both commemorative events and what has been called ‘apology activism.’

Advisor: Shanken, Andrew M
Gesture as a Dialogic Resource in STEM Instructional Interactions

When science, technology, engineering, and mathematics (STEM) students and educators interact, they draw on a variety of multimodal communicative resources including gesture, prosody, facial expression, gaze, and body positioning. This dissertation examines how educators and learners take up and interact with each other’s multimodal utterances in mathematics and computer science learning settings./nUsing multimodal microanalysis of video, I identify and characterize new forms and functions of gesture as a dialogic resource in these settings, building on previous work on dialogic gesture in different contexts. My analyses are informed by ethnomethodology and conversation analysis (EMCA) and the Co-Operative Action Framework, which provide key theoretical tools for understanding how participants reuse and transform components of each other’s multimodal utterances to make meaning together./nThis dissertation contains three papers. The first paper investigates different ways educators can repeat and reformulate learners’ gestures and speech in order to help learners make connections between their ideas and more formal ways of describing those ideas mathematically. My second paper explores how dialogic gesture functions to organize a common pattern of classroom dialogue—the Initiation-Response-Evaluation/Follow-up (IRE/F) sequence—and supports the co-construction of public knowledge in programming classrooms. Finally, my third paper builds on the previous two by illustrating additional ways educators attend to and engage with students’ multimodally-expressed ideas to help lead children towards new mathematical discoveries./nOverall, this dissertation contributes to learning theory by broadening our understanding of multimodal communication in STEM education. More specifically, it demonstrates the important roles dialogic gesture can play in STEM instruction, and it shows how responsiveness to students’ gestures is beneficial for learning mathematics and computer science. Numerous strategies for using dialogic gesture are provided that educators can adopt.

Advisor: Abrahamson, Dor
The Cybernetic Origins of Life

This dissertation elucidates the cybernetic response to the life question of post-World War II biology through an analysis of the writings and experiments of Warren S. McCulloch. The work of McCulloch, who was both a clinician and neurophysiologist, gave rise to what this dissertation refers to as a biological, medical cybernetics, influenced by vitalist conceptions of the organism as well as technical conceptions of the organ, the brain. This dissertation argues that the question ‘what is biological life?’ served as an organizing principle for the electrical, digital model of the brain submitted in “Of Digital Computers Called Brains” (1949) and the formal, mathematical model of the brain required by the McCulloch-Pitts neuron in “A Logical Calculus of the Ideas Immanent in Nervous Activity” (1943). I argue that, in discussions in these papers of how the brain responds to stimuli, there is a concept of biological life as perceptual life, rendering the brain a biological object with technical attributes whose activity is the activity of world-building. This dissertation analyzes experiments McCulloch performed on living animals to understand how the cybernetic brain was pharmacological and not merely digital or automatic. Finally, this dissertation analyzes writings on the discipline of biology published late in McCulloch’s life, which concern the information carrying capacity of water molecules, the reproductive protein called the “Biological Computer,” and a thought experiment on building a simulation of man. I claim that McCulloch’s “Biological Computer” includes a model of heredity counter to that of DNA, where form and not the program bears life forward.

Advisor: Bates, David
Geometric Sampling Theory, Triangulations, and Robust Machine Learning

Manifold triangulation is the problem of, given a set of points $V$ sampled densely from some known manifold $\Sigma$, output a set of simplices $\mathcal{T}$ that is topologically identical to $\Sigma$ and geometrically close to $\Sigma$. In the first part of this thesis we study a variant of this problem with one additional constraint. In addition to a set of points $V$ densely sampled from a known $\Sigma$ we are also given a finite set of line segments $S$, whose endpoints are in $V$, which must appear as edges in the output triangulation $\mathcal{T}$. To solve this problem we introduce \emph{restricted constrained Delaunay triangulations} (restricted CDTs), which combine ideas from constrained Delaunay triangulations and restricted Delaunay triangulations to enable the enforcement of constraining edges on triangulations of smooth surfaces. We prove several combinatorial properties of restricted CDTs, including conditions under which the restricted CDT contains every constraining segment, conditions under which the restricted CDT is homeomorphic to the underlying surface $\Sigma$, and a characterization of which vertices must be considered to compute the triangles near a segment. The restricted CDT has immediate practical applications in surface meshing and geometric modeling. Along the way we improve many commonly used supporting results in geometric sampling theory./nIn the second part of this thesis we apply the geometric tools and high-dimensional intuition developed in the previous chapters to problems in machine learning. We study the problem of adversarial examples, a pervasive phenomenon of machine learning models where perturbations of the input that are imperceptible to humans reliably lead to confident incorrect classifications. We study robustness to adversarial examples under the ``Manifold Hypothesis'': the observation that `real' data often exhibits low-dimensional structure. Our results highlight the role of codimension, the difference between the dimension of the data manifold and the dimension of the embedding space, in adversarial robustness. We prove a tradeoff between robustness in different norms, show that adversarial training is sample inefficient, and that robustness requires larger models./nLastly we study the relationship between robustness and optimization in the linear regression setting. We show an example of a learning problem for which the solution found by adaptive optimization algorithms exhibits qualitatively worse robustness properties against both $L_{2}$- and $L_{\infty}$-adversaries than the solution found by non-adaptive algorithms. Then we fully characterize the geometry of the loss landscape of $L_{2}$-adversarial training in least-squares linear regression. The geometry of the loss landscape is subtle and has important consequences for optimization algorithms.

Advisor: Shewchuk, Jonathan R
The rates and processes affecting the deposition of NOx to vegetation at leaf-level and canopy-level scales: impacts on NOx lifetimes and budgets in the troposphere

Both canopy-level field measurements and laboratory studies suggest that absorption of NO2 through the leaf stomata of vegetation is a significant sink of atmospheric NOx (NOx≡NO2+ NO), removing a large fraction of the global soil-emitted NOx. Understanding the mechanisms of NOx foliar loss is important for constraining surface ozone, constraining NOx mixing ratios, and assessing nitrogen inputs to ecosystems. However, the mechanisms of this foliar NO2 uptake and their impact on NOx lifetimes remains incompletely understood.To understand the leaf-level processes affecting ecosystem scale atmosphere-biosphere NOx exchange, I have conducted laboratory experiments of branch-level NO2 deposition fluxes to six coniferous and four broadleaf native California trees using a branch enclosure system with direct Laser Induced Fluorescence (LIF) detection of NO2, which excludes biases from other reactive nitrogen compounds and has a low detection limit of 5—50 ppt. I report NO2 foliar deposition that demonstrates a large degree of inter-species variability, with maximum observed deposition velocities ranging from 0.15—0.51 cm/s during the daytime, as well as significant stomatal opening during the night. I also find that the contribution of mesophyllic processing to the overall deposition rate of NO2 varies by tree species, but has an ultimately inconsequential impact on NOx budgets and lifetimes. Additionally, I report no evidence of any emission of NO2 from leaves, suggesting an effective uni-directional exchange of NOx between the atmosphere and vegetation.In parallel with these laboratory experiments, I have constructed a detailed 1-D atmospheric model to assess the contribution of leaf-level NOx deposition to the total NOx loss and canopy flux. My model is able to closely replicate canopy fluxes and above-canopy NOx daytime mixing ratios observed during two field campaigns, one in a western Sierra Nevada pine forest (BEARPEX-2009) and the other in a northern Michigan mixed hardwood forest (UMBS-2012). I present a conceptual argument for the importance of NO2 dry deposition and demonstrate that NO2 deposition can provide a mechanistic explanation for the canopy reduction of NOx. Using the leaf uptake rates measured in the laboratory, these modeling studies suggest that loss of NOx to deposition in forests competes with the pathways of HNO3 and alkyl nitrate (RONO2) formation, with deposition making up to∼40% of the total NOx loss. Additionally, foliar uptake of NOx at these rates could account for as much as∼60%canopy reduction of soil NOx emissions, reconciling inferences of canopy NOx reduction with leaf-level deposition processes. Finally, I show NO2 foliar deposition has a significant impact on ozone and nitrogen budgets under both high- and low-NOx conditions.

Advisor: Cohen, Ronald C
Multiplicative coding and factorization in vector symbolic models of cognition

This dissertation covers my attempts to confront the challenge and promise of multiplicative representations, and their attendant factorization problems, in the brain. This is grounded in a paradigm for modeling cognition that defines an algebra over high-dimensional vectors and presents a compelling factorization problem. The proposed solution to this problem, a recurrent neural network architecture called Resonator Networks, has several interesting properties that make it uniquely effective on this problem and may provide some principles for designing a new class of neural network models. I show some applications of multiplicative distributed codes for representing visual scenes and suggest how such representations may be a useful tool for unifying symbolic and connectionist theories of intelligence.

Advisor: Olshausen, Bruno A
Efros, Alexei
Design, Development and Applications of Portable Field Emission Devices

Vacuum tubes were integral to the rise of electronics in the 20th century, enabling the development of many core technologies, such as radar, television, radio and audio communications and early computers. However, the invention of the solid-state transistor, and subsequent integrated circuit technology, meant that electronics could be smaller, cheaper, faster and more reliable than vacuum tubes. Because of this, vacuum tubes were ultimately superseded by solid-state devices and thus began the trend of rapid miniaturization of electronics. Interestingly, although solid-state devices supplanted vacuum tubes in most domains, the trend towards miniaturization also enabled the emergence of vacuum microelectronics - a field that uses modern solid-state microfabrication techniques to develop micrometer-scale vacuum-based devices, or field emission devices. The emergence of this field was motivated by the desire to leverage some of the unique performance advantages offered by vacuum-based devices. Indeed, vacuum as an electron conduction medium offers some unique technical advantages over solid-state transport, such as ballistic electron transport, the ability to operate at high frequencies and robustness in harsh conditions, such as extreme temperatures, extreme pressures and high radiation environments. However, in order to leverage these features and enable widespread and practical use of field emission devices in electronics, on-chip ambient operation device architectures directly integrated on Si must be designed./nHere, the design and application of portable field emission devices that can operate in ambient conditions will be presented and discussed. This includes the first demonstration of vacuum-sealed fully integrated diode and triode field emission arrays that are developed in a scalable, BEOL-compatible process directly on Si. The device architectures demonstrate effective vacuum-sealing and gate-modulated field emission, with the ability to block voltages of up to 200 V. High operating voltages and low currents make these devices useful in high voltage drive circuits for MEMS actuators. Then, a novel device architecture for a portable electron source is presented. A fabrication process is developed to integrate graphene as an extraction electrode for field emission arrays on Si. Operation of this device is the first demonstration of a fully integrated field emission array utilizing graphene as both an extraction electrode and electron-transparent vacuum seal, enabling in-air extraction of electrons. The type of on-chip portable electron source developed here presents a unique method for using field emission-based electron sources in non-ideal conditions, unlocking applications ranging from ion thrusters for microrobotics to environmental microscopy.

Advisor: Subramanian, Vivek
Pister, Kristofer