VictorJuiz/thesis huggingface dataset:
USING AMBIENT MULTIPLE CHAPTER NARRATIVES TO MOTIVATE FITNESS BEHAVIOR CHANGE OVER TIME

Persuasive technologies have been proposed to address global health issues caused by lack of physical activity and the growing rate of sedentary lifestyles. However, existing systems are not effective in sustaining behavior change over time. To motivate behavior change toward healthier lifestyles, we have designed and developed WhoIsZuki, a mobile app which visualizes physical activities and goals as components of a multiple chapter graphic narrative that resides on an ambient display of users’ phones. Three formative studies including two survey studies and two rounds of one-on-one interviews have been conducted to inform project ideas, design of the system, and to improve narrative engagement and comprehension. A 3-week field trial is ongoing in which 16 participants use different designs of the system and report feedback about its ambient narratives and interface. The result of this 3-week field trial will inform the design of a 12-week field trial as well as provide broadly applicable design guidelines and implications for persuasive technologies that aim to motivate and sustain behavior change over time.

Keywords:  Symbolic Systems Program
behavior change
narrative persuasion
ambient display
Thesis
Advisor: Landay James
Crum Alia
Using generative deep learning to create high-quality models from 3D scans

With recent developments in both commodity range sensors as well as mixed reality devices, capturing and creating 3D models of the world around us has become increasingly important. As the world around us lives in a three-dimensional space, such 3D models will not only facilitate capture and display for content creation but also provide a basis for fundamental scene understanding, from semantic understanding to virtual interactions. Leveraging data from commodity range sensors to reconstruct 3D scans of a scene has shown significant promise towards 3D model creation of real-world environments. However, the quality of reconstructed 3D scans has yet to reach that of artist-created 3D models -- in particular, 3D scans always suffer from incompleteness, due to the many occlusions in real-world scenes as well as physical limitations of range sensors. Such incomplete 3D models are both unsuitable visually, and moreover, provides only a limited basis for higher-level scene reasoning. This work focuses on the task of scan completion, that is, from a 3D scan with partial geometry due to occlusions and scanning patterns, we aim to infer the missing geometry. We introduce a generative formulation for scan completion, leveraging deep learning techniques to create high-quality, complete models from 3D scans. We approach this problem as a conditional generative task, where we condition on an input partial scan and aim to learn `part'-wise similarity between scans to infer the complete model. First, we begin by focusing on the more constrained problem of completing scans of isolated shapes. We then expand upon this to design a generative approach for completion of general 3D scans of arbitrary scenes, directly addressing the challenge of varying scene sizes in 3D. This not only provides scan completion at scale, producing geometrically complete 3D models, but also provides a basis for higher-level scene reasoning such as that required for virtual interactions or physical simulations.

Advisor: Hanrahan P. M. (Patrick Matthew) 
Funkhouser Thomas 
Savarese Silvio
Variations in the oxygen fugacity of the Upper Mantle

Life thrives on our planet today because of the oxygen fugacity of the Earth's interior. Volcanic degassing of relatively oxidized C-O-H-S species helps sustain the oxygen-rich atmosphere that we breathe, while convection of reduced liquid Fe-Ni metal in the outer core generates the magnetic field that protects our planet from harmful radiation. On and within our planet alone, oxygen fugacity varies by over fifteen orders of magnitude, yet sub-log unit changes can have drastic effects on mineralogy, volatile speciation, and melting behavior within the Earth's mantle. In this thesis, I investigate the oxygen fugacity of upper mantle rocks (peridotites) dredged from the seafloor at convergent plate boundaries (subduction zones) and divergent plate boundaries (mid-ocean ridges). The first part of my thesis focuses on methodology—updating and refining the existing technique for determining oxygen fugacity in peridotites and demonstrating that this technique is applicable to even highly altered seafloor samples. In the remainder of the thesis, I present analyses of seafloor peridotites, primarily from the Tonga subduction zone in the South Pacific and the Southwest Indian Ridge in the southern Indian Ocean. My datasets are unique in that they document the oxygen fugacity of these geographic locations with unprecedented spatial density, allowing me to interrogate variability that was previously obscured by sparse global sampling. I show that the mantle beneath subduction zones gains its uniquely oxidized signature upon interaction with subduction-related melts and fluids. I additionally demonstrate that once changes related to a peridotite's thermal history are taken into account, mid-ocean ridge peridotites imply an average upper mantle oxygen fugacity consistent with that implied by mid-ocean ridge basaltic magmas. Finally, I show previously undocumented heterogeneity in the range of oxygen fugacity recorded by seafloor peridotites, indicating a vast complexity to the behavior of oxygen within our planet's interior.

Keywords: Geological and Environmental Sciences.
Advisor: Mao Wendy (Wendy Li-wen) 
Warren Jessica
Brown G. E. (Gordon E.)
Cottrell Elizabeth
Stebbins Jonathan Farwell
Viral Taxonomy Derived From Evolutionary Genome Relationships

We describe a new genome alignment-based model for classification of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of k-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified.

Keywords:  Department of Physics
Virus Taxonomy
Thesis
Advisor: Quake Stephen
Schleier-Smith Monika
Visibility policy, seller incentives, and pricing dynamics in a digital goods marketplace

There has been rapid growth in digital goods platform-marketplaces such as the Apple App Store or Google Play store, partially driven by low barriers to entry for new and entrepreneuring developers looking to sell their products. These small and independent sellers rely on marketplace mechanisms for product discovery in the absence of the means or ability to advertise. App store markets frequently link visibility and discovery to historical sales: top selling products are featured more prominently on frontpage and search results. Similar mechanisms are present in many online store contexts. Yet, their impact on marketplace outcomes has largely been understudied in the literature. This research aims to bridge this gap using data from a large app store-like marketplace to examine the implications of this common marketplace visibility policy. I present a model in which the visibility policy is internalized by sellers in their pricing decisions and incorporate rich institutional details from the marketplace to aid in estimation. Using this model, I show that marketplace policy leads sellers to compete for visibility by adopting strategies of lowered introductory pricing. The widespread use of introductory pricing strategies leads to inefficient pricing from an aggregate perspective, reducing seller revenue and thereby the marketplace operator's revenue share. This issue can be thought of as a form of channel conflict from the perspective of the marketplace operator, whereby the operator in the role of the wholesaler would like to enforce a higher price level but is thwarted by seller (retailer) competition for visibility. I evaluate a mitigation strategy the marketplace operator could pursue - ranking products by revenue rather than sales quantity - through counterfactual simulation and find that the marketplace operator could increase revenue 13% by switching ranking algorithms, though at the cost of consumer welfare and among other implications.

Keywords: Business.
Advisor: Narayanan Sridhar
Johari Ramesh
Nair Harikesh S. (Harikesh Sasikumar)
Visual understanding of human activity : towards ambient intelligence in AI-assisted hospitals

Ambient intelligence infused in the physical space of buildings and structures aims to make them perceptive and reactive, able to dynamically provide assistance to humans in environments ranging from homes to hospitals. A key requirement towards this is visual interpretation of human activity captured by visual sensors embedded in the physical spaces. In order to provide humans with appropriate assistance, we must develop the computer vision algorithms that can recognize what humans are doing at every moment in time, across diverse and fine-grained activities and despite challenging viewpoints and computational constraints. In this thesis, I present computer vision algorithms that push our capabilities towards ambient intelligence. In the first part of the thesis, I tackle major technical challenges of contextual awareness, embedded vision, and adaptivity, in the context of recognizing human activities. I introduce methods for dense and detailed interpretation of human activity, for efficient detection of actions, and for learning about new human actions from few labeled training examples. Then in the second part of the thesis, I present my work on a real-world prototype of ambient intelligence: AI-Assisted Hospitals where computer vision algorithms are used to provide continuous awareness of clinical activities. I describe two proof-of-concepts, monitoring hand hygiene and documenting patient mobility care activities. These reflect the potential of computer vision and ambient intelligence to assist clinicians and healthcare workers across rich and diverse use cases.

Keywords: Electrical Engineering.
Advisor: Li Fei Fei
Milstein Arnold
Nishimura Dwight George 
Wetzstein Gordon
Visualizing Gentrification

This is a web-based application that visualizes gentrification in the United States based on Census data from the 2011 and 2016 American Community Surveys. Using an index based on Census data, the application allows users to visualize the factors that affect gentrification for a specific U.S. geography (city, state and/or Census tract). The application is available for use at https://www.gentriviz.com.

Keywords:  Department of Communication
Gentrification
Department of Communication
Graduate Program in Journalism
School of Humanities and Sciences
census
Thesis
Advisor: Nguyen Dan
Waiting room: a feminist theatre-making Practice & Waiting room: A verbatim play

Interviews with nine individuals about their experiences undergoing surgery to remove their breasts have been edited and transformed into a verbatim theatre script. The author uses feminist interviewing techniques and places people of different ages and genders in conversation with one another about an experience they share. This document includes a paper detailing the author's research process and personal relationship to the project and a draft of the script that was completed in June 2018.

Keywords: breasts
mastectomy
breast cancer
gender dysphoria
transgender
top surgery
verbatim theatre
Feminist Gender and Sexuality Studies
Thesis
Advisor: Pufahl Shannon
Hanlon-Baker Patti
Crandall Maxe
Waveform design for charge pumps in energy harvesting systems

Wireless energy harvesting devices convert received AC energy into DC voltages suitable to power the back-end functionality of the devices. The low energy available to the devices require high AC-DC conversion efficiency in order for enough power to be delivered to the load. However, models to accurately predict charge pump performance, especially across waveform shape, for energy harvesting systems are limited. In this work, we will first present a model to characterize loss through charge pump cells in wireless energy harvesting devices. The proposed model includes the time-domain effects of the input radio-frequency (RF) energy wave and provides additional insight into how clock and switch parameters along with architecture considerations can be used to improve the efficiency of AC-DC conversion. We compare the performance between sine-wave and square-wave clocked charge pumps to show the trade-off between charge pump loss and clock generation power consumption. We will then show the benefits of using multi-tone waveforms and present a pathway to determining an arbitrary input waveform.

Keywords: Electrical Engineering.
Advisor: Poon Ada Shuk Yan
Pauly John (John M.) 
Wong S. Simon
What do microglia do? New tools for the study of rodent and human microglia

The specific function of microglia, the tissue resident macrophages of the brain and spinal cord, has been difficult to ascertain due to a lack of tools that distinguish microglia from other immune cells, thereby limiting their specific immunostaining, purification, and manipulation. Due to their unique developmental origins and predicted functions, the distinction of microglia from other myeloid cells is critically important to understanding brain development and disease; better tools would greatly facilitate studies of microglia function in the developing, adult, and injured CNS. This thesis consists of two main parts. The first is dedicated to identifying Transmembrane Protein 119 (Tmem119), a cell surface protein of unknown function, as a highly expressed microglia-specific marker in both mouse and human. In this section, I provide background information about microglia, the current state of research, and the importance of a molecular marker of microglia to better understand their function. I then discuss the qualities important for a unique molecular marker and show that, by RNA, Tmem119 fulfills these in both mouse and human. I discuss the development of monoclonal antibodies to the intracellular and extracellular domains of Tmem119 that together enable the immunostaining of microglia in histological sections in healthy and diseased brains and the isolation of mouse microglia by FACS. In the second part, I use these antibodies to generate the first RNAseq profiles of highly pure mouse microglia during development and after an immune challenge. I optimized an isolation protocol that reduces baseline microglial activation to better capture the in vivo genetic profiles of microglia. I found that mouse microglia mature by the second postnatal week, and that this maturation both corresponds with Tmem119 immunoreactivity and correlates with the expression of many microglia-enriched genes. I identified genes which are differentially expressed during development, after immune challenge, or between microglia and other macrophages. I generated several lists of genes containing enriched transcription factors, receptor-ligands, and disease-related genes. I also generated a resource, available at www.BrainRNAseq.org for scientists to mine these data themselves. Through these analyses, we made several new predictions about the functions of microglia - including a potential role in hemostasis. Finally, in the closing chapters, I discuss future directions and some preliminary work to harness these insights for future work - understanding the function of this highly specific and enriched gene, developing genetic tools to study microglia in vivo, and ultimately - to better understand what microglia do.

Advisor: Barres Ben
Shatz Carla J. 
Palmer Theo 
Porteus Matthew H.
Wyss-Coray Anton
What does an interruption sound like?

Taking turns is fundamental to conversation. When people participate in a conversation, they alternate between moments of speaking and not speaking, and generally, only one person at a time claims the role of speaker. It has long been argued that attempting to avoid moments where two or more people speak at the same time is a universal norm for conversation with both cognitive and social motivations. Despite this, moments of simultaneous, overlapping speech are relatively common in everyday conversation and can occur without diminishing comprehensibility or violating social norms. This has provoked a great deal of research which asks: When is it acceptable for more than one person to speak at the same time, and when is it disruptive? In other words, when does overlapping speech constitute an interruption? I argue that the answer to this question is inherently subjective and influenced by a person's own conversational style. Moreover, because conversation participants take turns carrying out actions which extend beyond the scope of a single speaking turn—such as telling a story or solving a problem—I argue that speakers can interrupt by disrupting the completion of such an action, even when they do not speak at the same time as another person. This dissertation uses a large-scale social perception experiment to analyze how listeners come to the interpretation that an interruption has occurred in conversation. I find that listeners perceived speakers to be interrupting when they overlapped with their interlocutors for an extended period of time while also using louder voice and faster speaking rate. However, these perceptions varied depending on the listeners' own conversational styles and were more heavily influenced by the pragmatic relations between speaking turns than even the degree of overlap between turns. Based on these findings, I argue that, rather than being an objectively measurable property of the speech signal, interruptions are subjective and context-dependent interpretations about who has the right to speak at a particular moment in time about a particular topic.

Keywords: Linguistics.
Advisor: Podesva Robert 
Eckert Penelope 
Sumner Meghan
What Makes Korean Software Engineers Continue to Stay in Silicon Valley?

This thesis seeks to understand what prevents Korean software engineers from returning to South Korea and examines the motivations and concerns that Korean software engineers have in deciding whether to return to Korea or remain in Silicon Valley. Because Silicon Valley is known for attracting top foreign skilled talent, the Korean government has made many attempts to mirror Silicon Valley’s startup environment in places such as Pangyo and Ayang (SBS News, 2013). As a result, I had initially hypothesized that Korean software engineers desired to stay in the U.S. primarily due to their attraction to Silicon Valley’s innovative and startup environments. Instead, key identifying factors that made Korean software engineers desire to continue working and living in Silicon Valley included higher paying salaries than those in South Korea, better cost and quality of living, stable residency status, self-identity, and participant status. My research thesis will be outlined as follows.
My research thesis acquired demographic data on a sample size of 100 Korean international software engineers who have already left South Korea to work in Silicon Valley in order to better understand what has made them decide against physically returning back to South Korea. My thesis research (i) provides background information on brain drain in South Korea, (ii) how the causes of brain drain are different today, (iii) what South Korean policymakers have been doing in attempts to reverse brain drain both in the past and currently, (iv) present key empirical and qualitative findings, (v) present limitations from my survey results, and (vi) concludes with suggestions on turning brain drain into brain circulation and brain linkage based on the findings from my thesis research. Ultimately, the goal of this research is to provide more insight on what drives these Korean software engineers to continue working in Silicon Valley. It is my hope that such insights will allow for more relevant suggestions on how to turn this brain drain into brain circulation and brain linkages.

Keywords:  Stanford Global Studies
Center for East Asian Studies
Brain Drain
Brain Circulation
Brain Linkage
Korean software engineers
Silicon Valley
Thesis
Advisor: Shin Gi-wook
“What right had Caesar to the empery?”: Power and the Individual in Plays of Christopher Marlowe

This honors thesis is a powerful interrogation of "radical individuality" in two plays by renegade Renaissance playwright Christopher Marlowe. This thesis covers a wealth of historical and dramatic terrain, and blends "close reading" with "distant reading" in its analysis and argument. It questions why Marlowe has not received significant attention by New Historicists; nor has Digital Humanities seen fit to bend its practices to Marlowe's plays. The first chapter discusses Dr. Faustus through various close readings, Cultural Materialism, and New Historicism. The second chapter is a Digital Humanities inquiry into The Jew of Malta. It utilizes network analysis to discuss various characters' spheres of influence.

Keywords: Christopher Marlowe
New Historicism
Cultural Materialism
Dr. Faustus
Jew of Malta
Massacre at Paris
English Undergrad Honors Thesis
Thesis
What’s in the air you breathe?: California tackles air pollution disparities with data, policy efforts

While California holds a reputation as a leader in environmental policy, it still ranks worst out of all 50 states for average public exposure to particulate matter pollution — largely due to the state’s topography and dense population. California is also home to 8 of the 10 U.S. metropolitan areas with the highest year-round concentration of particulate matter. In 2017, the Bay Area ranked fourth on the list, above the notoriously polluted Los Angeles-Long Beach area. And though overall air quality statewide is improving, there are communities where pollution levels are the same or worse.
Today, understanding air quality at a hyperlocal level is a major challenge for both local residents and public officials. Data monitoring stations are few and far between, taking regional air measurements that differ drastically from what an individual may be actually breathing at any given time. As population and traffic congestion in the Bay Area grow, existing infrastructure keeps many local schools and athletic facilities a stone’s throw from emissions-heavy freeway routes. And as has been well-documented, low-income areas and communities of color face stronger impacts from polluted air.
Startups and government agencies are working to improve data collection on air quality statewide, while policymakers attempt to close the disparity in pollution levels between wealthy and disadvantaged communities. But as they do so, future wildfires like those that tore through the North Bay in 2017 threaten to set back the state's efforts to clean up the air.

Keywords:  Department of Communication and Journalism
Stanford University Department of Communication
Master's in Journalism Program
environmental justice
air pollution
public health
California
Thesis
Advisor: Zacharia Janine