VictorJuiz/thesis huggingface dataset:
Exploiting contact dynamics for grasping and anchoring in the field
Keywords: Engineering.
Mechanical Engineering.

This thesis is about how to equip robotic platforms with the capability to forcefully interact with their environments. These forceful interactions often entail designing grippers or end-effectors that can grasp or anchor to different environmental features. When designing these grippers, the general design approach has four common considerations. The first is the contact dynamics, where the gripper interacts with the surface. This includes both the contact mechanics at the surface and the dynamics caused by the interaction. The second is how to achieve the desired surface conformity between the gripper and the often irregular contact surface. The third is the incorporation of load sharing elements to uniformly distribute the interaction force across the contact area, especially in the case where astrictive contact dynamics are used. Last, we consider how the integrated system should respond to the dynamic interaction to achieve the desired system response. In this thesis, we present three different mobile robots intended for operations in the field with forceful interaction. Although they are different platforms, the design approach of their grippers is consistent and can be applied to many other different robotic platforms and field scenarios. The first of these robot platforms is Astrobee, a free-flying robot inside of the International Space Station (ISS). A gripper was designed for Astrobee and allowed it to grasp and perch onto flat surfaces inside of the ISS with gecko-inspired adhesives. The second gripper enabled a quadrotor to capture a flying target. We define a velocity sufficiency region of acceptable initial conditions immediately prior to contact and show that the incorporation of passive mechanisms greatly expands the region. Last, a new climbing robot concept, ReachBot, is designed for interaction with rocky caves. ReachBot is a robot that consists of a small body with long limbs created by extendable booms. We present the system design considerations, a planar prototype, and tests conducted with a partial (single arm) 3D system prototype with a microspine gripper in the Mojave Desert. In these examples, the dynamic interaction results in limits in the force space that must be satisfied to achieve successful grasping. Then, along with the incorporation of passive mechanisms, one can create a sufficiency region of possible initial conditions immediately prior to the contact, with a probability of grasp success. This approach to modeling and passive mechanism design can simplify the control of the robot and inform future design iterations and modifications to meet the requirements of other robotic platforms.
Exploiting linearity to precisely control a vehicle about an unstable equilibrium
Keywords: Engineering.
Mechanical Engineering.

Drifting - operating a vehicle at a high sideslip angle - offers intriguing possibilities for controlling autonomous vehicles in critical situations. While drifting is a very dynamic process, occurring in a region of the state space with saturated tires and unstable equilibria, autonomous vehicles have been successfully controlled in this region. Many previous control approaches to path tracking while drifting have relied on nonlinear vehicle models. This thesis, however, demonstrates that linearized models capture the necessary dynamics for control in a large region surrounding a drift equilibrium. Furthermore, the eigenstructure moving from one equilibrium to the next is very consistent, enabling control not just around a single drift equilibrium but throughout this region of the state space. Using this linearized model, in which the longitudinal velocity is assumed to be maintained constant using the front brakes, a controller based on a linear quadratic regulator is developed. This controller uses steering, throttle, and brakes, making the system fully actuated and able to simultaneously track a velocity and sideslip profile while following a reference path. The fidelity of this linearized model and the utility of this controller are demonstrated by implementing this controller on MARTY, an electric DMC DeLorean. This linear controller accurately tracks equilibrium and quasi-equilibrium paths with centimeter-level accuracy that exceeds prior work with more complex nonlinear models and control techniques. Incorporating linear dynamics with variable speed drifting and removing the constant longitudinal velocity assumption tests the limits of this new linearized model. Additionally, incorporating wheel speed dynamics makes this controller functional for an internal combustion engine vehicle. This new fully actuated controller with variable speed linear dynamics uses a linear quadratic regulator framework and is demonstrated on Takumi, a Toyota Supra with an internal combustion engine. Experimental tracking error results again exceed previous work with nonlinear models and control techniques. While the addition of a feedforward term can minimize tracking error during transient sections of quasi-equilibrium paths, a new control framework is needed to further improve results. Accordingly, a model predictive controller is developed using the same linear model. This new control framework that optimizes the inputs over a finite horizon allows the controller to incorporate the reference trajectory and actuator constraints. By incorporating this additional information into the control framework, the input commands stay within actuator constraints even during transient portions of the reference path. This fully actuated model predictive controller is demonstrated on Takumi. This series of controllers each highlights the utility of this linearized model near unstable equilibria and demonstrates that this simple model can lead to better path tracking results than controllers developed using more complex nonlinear models
Exploring Moiré Transition Metal Dichalcogenide Heterostructures
Keywords: Physics
Transition metal dichalcogenide
Moiré heterostructure
Heterobilayer
WS2/WSe2
Superlattices
Text
Thesis

In recent years moiré transition metal dichalogenide (TMD) heterostructures have been studied extensively, realizing a tunable platform to study electronic correlations. In this thesis, we describe efforts to develop new moiré TMD device architectures to study and tune interacting ground states and characterize them using electrical transport measurements. We focus in particular on a novel geometry, using bilayer graphene as a sensing layer to measure the chemical potential of a WS2/WSe2 heterobilayer. We observe interaction-driven gaps in the TMD bilayer in agreement with previous work upon both electron and hole doping. We also discuss preliminary attempts to tune the TMD superlattice potential and Coulomb screening in situ, though these remain inconclusive so far. Our work highlights some of the experimental challenges involved in fabricating moiré TMD devices, and we end with an outlook on improving future devices.
Exploring the introduction of real-life usages of Japanese honorifics in foreign language study
Keywords: Humanities and Sciences.
East Asian Languages and Cultures.

The current dissertation investigates factors that influence usages of Japanese honorifics and explores how instructors can introduce honorifics more effectively to second-language learners. Apart from existing literature, my data includes a corpus of real-life usages of Modern Japanese, classroom observations, interviews with Japanese language instructors, and a workshop conducted as an implementation of new pedagogy. I first examine the definition of honorifics and relevant concepts such as expressions of personal treatment and speech levels. Using diverse usages in real life, I examine multiple layers of meanings associated with honorifics and propose factors that influence usages of honorifics. My analysis suggests that usages of honorifics do not always match their labels, and that honorifics may be used for various purposes. In the latter half of this dissertation, I lay out existing pedagogy and discuss challenges in teaching Japanese honorifics. In addition, how mainstream textbooks introduce honorifics is also reviewed. After qualitatively discussing first-hand data, I make suggestions for introducing Japanese honorifics to learners of different proficiency levels. Bridging latest research on honorifics to teaching practices in second-language classrooms, my main teaching goal is that students will be able to use honorifics to express themselves instead of blindly following normative rules introduced in textbooks.
Exploring the many scales of neural activity underlying perception and decision making
Keywords: Humanities and Sciences.
Applied Physics.

Experimental technologies that probe neural circuits from single neuron to brain-wide scales have allowed us to deepen our understanding of neural phenomena ranging from perception to decision making. For example in visual perception, orientation tuning in primary visual cortex (V1) has long been thought to play an important functional role in perception, but tests of this role have only recently been made possible through direct optogenetic stimulation of mouse cortex. Indeed, optogenetic stimulation reveals that a surprisingly small number of excited neurons (~20) can drive both large-scale neural ensembles (~1000) and perception. We develop a mean field neural circuit theory for how such small stimulation can create large responses. Our theory also explains constraints on avalanche like behavior widely observed in the spontaneous activity of many species. We further study decision-making at a global-brain scale leveraging multi-region neuropixel recordings collected across a collaboration of 11 experimental labs (part of "the International Brain Lab" (IBL)). We analyzed a massive dataset consisting of the neural activity of 300,000 neurons in mice performing a decision making task and developed techniques to elucidate the contribution of many different brain regions to decision making. Through decoding analyses, we discovered that task and behavioral variables can be decoded from regions which are both classically known as well as other regions which are functionally surprising. Overall, through theoretical analysis of unprecedented datasets, we propose a mechanism for perception in V1 and uncover region-specific details of brain-wide activity underlying decision making.
Fast decarbonization in a cost-based wholesale power framework: the case of Chile
Keywords: Public Policy
Energy
Wholesale Power
Energy Transition
Market Design
Electricity Markets
Chile
Renewable Energy
Stanford University
Humanities and Sciences
Public Policy Program
Text
Thesis

This study provides an extensive examination of the Chilean power generation market in the last eight years, with a particular focus on the impact of renewable energy sources such as solar and wind on traditional power generation and in the total producer surplus in the short-term market. The research highlights the changing operating patterns of traditional power plants, with a general trend of following net demand, and a corresponding increase in heat rates.
Key figures from the study indicate that, despite the retirement of inefficient coal units and the operation of more efficient ones, heat rates have been increasing, likely due to the higher variability in operation. Moreover, there has been a clear change in the operating pattern of coal based units, from a stable base load, to an hourly variable scheme following net demand. Similar changes have experienced some hydroelectric power plants.
The study also explores the producer surplus in the Chilean short-term market, showing two main findings. First, due to their high correlation and systemic character, solar generation impacts on spot prices has significantly decreased the average perceived price by that technology, unlike other renewable sources such as wind and hydroelectric. Second, under the current cost-based wholesale market design, all zero-cost generation shocks produce a negative impact on total producer surplus, with a small magnitude until the shock becomes relevant. When the generation of zero-marginal cost source is large as a proportion of the demand, the impact on producer surplus becomes disproportionately big.
The research underscores the significant role of ancillary services in the power generation segment, which have grown significantly in recent years. These services, although outside the spot market, contribute to the variable costs in the power generation segment.
The findings might have important implications for energy policy and future research, particularly in the context of renewable energy integration and the pursuit of sustainable and efficient energy systems. The study also underscores the need for further research into the theoretical underpinnings of the quantitative impact of zero-marginal cost generation shocks on producer surplus and short-term prices.
Feature-prompting Protocols for Data-driven Health Estimation and Lifetime Prediction of Lithium Metal Batteries
Keywords: Li-metal battery
health estimation
lifetime prediction
Machine learning
Text
Thesis

Lithium metal batteries (LMB) represent one of the most promising battery technologies due to their high energy density. However, the commercial adoption of LMBs has been hindered by their limited lifespan and safety concerns resulting from lithium metal’s high electrochemical reactivity. Effective health estimation and lifetime prediction could enable timely maintenance actions before failure and a rapid LMB development iteration. In this work, we first propose novel diagnostic test and aging cycling protocols that enable the tracking of LMB degradation from voltage-current measurements through extracting internal resistance, relaxation voltage, and charging impedance. With these features, we present an automatic data-driven aging modeling framework for LMBs. Validation over test cells demonstrate accurate health estimation performance using only one cycle of voltage and current data, and reliable lifetime prediction using cells’ early-life data. The proposed model provides explanatory insights tailored to LMBs, and does not require additional internal state sensors.
Felt design : inclusive practices for movement-based musical instruments
Keywords: Humanities and Sciences.
Music.

The expression of the moving body not only exists in music interaction and performance but also diversifies the practice of music-making. The majority of instrumental practice centers around the hearing culture, limiting communities with diverse abilities to access music creativity and performance. However, integrating body movements and kinesthetic expression increases inclusion and participation beyond the hearing culture. In this thesis, we incorporate wearable interfaces into digital musical instrument design to develop more inclusive instrumental practice and to create opportunities for bodily felt experiences through movement-based interactions. This research practice considers designing for, and from, the felt experience of the moving body in musical interaction. We refer to body-centric design methodologies from movement-based interaction and somaesthetics by applying these practices into the design of two movement-based musical instruments and one wearable vibrotactile interface. The thesis addresses the research questions about techniques to develop design practices for new musical instruments that highlight the felt and subjective experience of the moving body. The first project delves into an unexplored area in gestural interaction between nuanced musical interactions and expressive full-body movements by developing Bodyharp. The instrument provides an extensive opportunity to investigate the relationship between dance- and music-related movements, the performer roles of a musician and a mover, and the agency between an instrument and a body. It also emerges inclusive applications of movement-based design in music. In the second project, we create inclusive listening and performance contexts for increased accessibility and diversity across abilities. Felt Sound creates a listening experience for d/Deaf and Hard of Hearing (DHH) as well as hearing communities through shared performance experiences. We develop Touch, Listen, (Re)Act to bring this instrument into a co-design and performative setting to collaborate with a Deaf dancer, resulting in a shared language and mapping across music, movement, sign, and dance expressions. This research contributes to the fields of embodied HCI, music interaction, and movement-based design. First, we present the design framework and principles of Borrowed Gestures by studying the unexplored area between nuanced music-related gestures and larger dance-like body movements, rethinking the musical instrument as an extension of the body. We further develop a series of new digital musical instruments from body-based interfaces and physical laptop instruments to accessible, tangible, and tactile interfaces. Not only the design practice but also the co-design studies behind these musical instruments show their inclusive applications in working with diverse hearing communities. These efforts toward designing for social accessibility unfold some of the important practices that increase the active participation of DHH artists in music.
Finding Brick Kilns from Space: A Geovisual Search Pipeline
Keywords: Brooks, Nina
Ermon, Stefano
computer science
machine learning
computer vision
sustainability
health
Text
Thesis

Brick production is central to economic development in Bangladesh. The industry is dominated by traditional brick kilns that generate substantial environmental and human health harms. Despite numerous regulations governing where brick kilns can be established and the type of manufacturing processes used, brick kilns are poorly regulated and tracked by the government. A lack of objective data on how many kilns exist, what type of technology is used, and where they are located inhibits ef- fective governance. Yet obtaining this type of data is difficult given the low-capacity of the government. We address these limitations by taking advantage of advances in machine learning and satellite imagery to develop a scalable and replicable geovisual search pipeline to visually identify all of the brick kilns in Bangladesh. By taking a weakly supervised approach to localization, we create a model that detects kilns using only sparse classification data. We also introduce an approach for scaling that can significantly improve the efficiency of models run on satellite imagery.
Fine-grained importance for perceptual video compression
Keywords: Engineering.
Electrical Engineering.

The proliferation of videos that are consumed by humans over the internet has accelerated the search for better video compression algorithms. Traditional video compression algorithms reduce video file sizes by removing spatial, temporal, and coding redundancies. Because different spatio-temporal regions of the video differ in their relative importance to the human viewer, there is an opportunity to improve video compression algorithms even further, by removing perceptual redundancy. However, it is challenging to infer what the levels of importance are to the viewer in different areas, or to even collect such fine-grained information. Indeed, such information is often not used during compression beyond low-level heuristics. In this dissertation, we present a framework that facilitates research into fine-grained subjective importance in compressed videos, which we have utilized to improve the rate-distortion performance of existing video codecs. The specific contributions of the work presented in this dissertation are threefold: (1) we designed a novel tool, the Perceptual Importance Map collection Tool (PIMTool), an interactive web-tool which allows scalable collection of fine-grained perceptual importance by having users interactively paint spatio-temporal maps over encoded videos. While users use the tool, the videos presented to the users are constantly updated based on their painted spatio-temporal maps, showing the users the trade-off between improving the importance of certain areas and decreasing the importance of other areas. This tool also allows users to control the magnitude of increase or decrease of the importance in different areas in the video, resulting in detailed relative importance maps; (2) Using PIMTool, we collected a dataset of 178 videos with a total of 14443 frames of human annotated spatio-temporal importance maps over the videos. We call this dataset the Perceptual Importance Map Dataset (PIMD). Via a subjective study, we demonstrate that encoding the videos in our dataset while taking into account the importance maps leads to higher perceptual quality at the same bitrate, with the videos encoded with importance maps preferred 1.8x over the baseline videos; and (3) we used our curated dataset to train a lightweight machine learning model that can predict these spatio-temporal importance regions. We call this model the Perceptual Importance Map Model (PIMM). Our results show that for the 18 videos in our test set, the importance maps predicted by our PIMM model lead to higher perceptual quality videos, 2x preferred over the baseline at the same bitrate
Flexible electronics as a platform for neuroscience : exploring the dynamics of aging, neurodegeneration, and novel animal models
Keywords: Humanities and Sciences.
Applied Physics.

Fundamental knowledge about the brain is primarily acquired through two distinct groups of methods. Techniques with low spatiotemporal resolution, such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), have provided insights into meso- and macroscopic neural activity. Owing to their noninvasiveness and growing availability to the general population, these techniques enable longitudinal studies of changes in brain states in the same individuals. Conversely, high spatiotemporal resolution techniques, such as single-neuron electrophysiology and imaging, have facilitated a deep understanding of the basic building blocks of the brain, from individual ion channels to single-neuron activity, and to region-wide dynamics of neuronal circuitry. However, high spatiotemporal techniques have largely been precluded from translating to long-term studies because of their invasiveness and a mismatch of properties with neural tissue. This spatiotemporal span (cross-sectional vs. longitudinal) and resolution gap has led to a significant division in our exploration of the brain's dynamics. This dissertation aims to explore flexible electronics, a recently developed electrophysiology tool, as a platform for bridging this very gap to enable a new longitudinal understanding of the brain at the single-neuron resolution. In Chapter 1, I provide background on the electric basis of neuronal communication, a historical perspective on methods used to electrically interface with the nervous system, and present an argument for developing more compliant, brain-like neural probes. Chapter 2 introduces flexible electronics as a competitive class of neural probes for interfacing with the brain as compared with conventional neurotechnologies and reviews the properties and previous applications of bioinspired, brain-like mesh electronics. In Chapter 3, I present key hardware improvements made to the mesh electronics platform to enable chronic interfacing with the brain. Chapter 4 reviews work conducted to facilitate simultaneous electrophysiology and behavioral neuroscience through the integration of a virtual reality (VR) system. Chapter 5 is centered around work measuring the longitudinal neural correlates of aging and neurodegeneration in wildtype (WT) and 3xTg Alzheimer's Disease (AD) mouse models, respectively. In Chapter 6, I introduce a novel application of mesh electronics to studying spatial cognition in a nonstandard amphibian model, the cane toad (Rhinella marina). Finally, I present a broad outlook for the future of flexible electronics and its applications to neuroscience.