VictorJuiz/thesis huggingface dataset:
Mid-infrared laser absorption spectroscopy for carbon oxides in harsh environments [electronic resource]

Advancements in measurement science are presented regarding in situ laser-based detection of CO and CO2 in harsh combustion environments. Mid-infrared absorption sensing strategies, utilizing transitions in the 2.7 and 4.3 micron vibrational bands for CO2 and the 4.8 micron vibrational band for CO, were developed to enable sensitive measurements of temperature and carbon oxide concentrations in high-temperature gases. These new strategies (1) extend the utility of carbon oxide absorption sensing for hostile aeroengine applications and (2) offer significant improvements to previous methods for shock tube kinetics studies. The recent maturation of mid-infrared diode and quantum cascade lasers, combined with parallel progress in mid-infrared fiber optics, provides the platform from which the field-deployable sensors were designed. State-of-the art signal processing strategies, including calibration-free wavelength modulation spectroscopy, were implemented to tackle the thermo-mechanically harsh environments of a pulse detonation combustor and directconnect scramjet. Time-resolved and spatially-resolved measurements of temperature and carbon oxide species concentrations were demonstrated to provide an in situ metric to evaluate combustion completion for engine development. For shock tube kinetics studies, a multi-band CO2 sensing strategy was developed to provide ppm-level species detection and highly-sensitive measurements of gas temperature with microsecond temporal resolution.

Keywords: Mechanical Engineering.
Advisor: Hanson Ronald primary advisor. Thesis advisor
Cappelli Mark A. (Mark Antony) advisor. Thesis advisor
Jeffries Jay Barker advisor. Thesis advisor
Mind matters [electronic resource] : how an intelligent in-vehicle agent can help female drivers under stereotype threat

This dissertation investigates how an intelligent in-vehicle agent can help female drivers under performance pressure by offering appropriate appraisal feedback on their experiences of failure in a driving task. In particular, the current work examines the effects of appraisal types provided by the agent on drivers' performance under stereotype threat. Study 1 examined the effects of stereotype threat (stereotype threat: threat vs. no threat) and attribution type (agent's attribution: internal vs. external) in a between-participants design (N=52). There was a significant interaction effect between stereotype threat and attribution type on performance. When female participants were under stereotype threat, external attributions of failure increased participants' driving performance. On the other hand, internal attributions of failure improved performance among those not under stereotype threat. Study 2 extended Study 1 by adding one more variable, mindset (fixed mindset vs. growth mindset), to the model. The results showed that failure appraisals with a growth mindset can lead to enhanced performance in general. Furthermore, the mindset moderated the stereotype threat effects. When participants were provided with appraisals with a growth mindset, their performance was not inhibited by the presence of stereotype threat. In addition, the mindset moderated the effects of attributions on performance. Participants in the fixed mindset condition drove worse when failure was attributed to others than to the self. However, participants in the growth mindset did not show a significant difference on performance based on the attribution type.

Keywords: Communication.
Advisor: Hamilton James
Reeves Byron
Schwartz Dan
Turner Fred advisor. Thesis advisor
Minimizing the effects of distortion and noise in fiber-optic communications and interferometric imaging through digital signal processing [electronic resource]

In this dissertation we will study the effects of distortion and noise in fiber-optic communications and interferometric imaging and methods to reduce their impact. In the area of fiber-optic communications, we will explore the two most economically significant applications: intra-data center links and optical access networks. The motivation for this study is the imminent need for optical links to undergo a large-scale upgrade in capacity to meet the needs of exponentially-growing Internet traffic. As these markets are high-volume and low-cost, we favor techniques which emphasize digital signal processing (DSP) over optical signal processing. The ability to transition to heavily DSP-based architectures is now possible due to recent development of commercial CMOS digital-to-analog and analog-to-digital converters with up to 65 Gsample/s conversion rates. However, such ultra-high-speed converters have limitations in resolution, and so we will investigate methods to compensate for this deficiency. In particular, we will introduce a new method of spectral reshaping to greatly increase a transmitter's signal-to-noise ratio when limited by a low-resolution digital-to-analog converter. Next we will discuss a novel architecture which enables electronic dispersion compensation in optical access networks using minimal opto-electronic components. We will present simulation and experimental measurement of record bit rates in a single polarization and wavelength using a receiver based on single-photodiode detection. The third topic within fiber-optic communications relates to intra-data center communications. For this application, chromatic dispersion is minimal and thus direct modulation of distributed feedback lasers is preferred, as it eliminates the need for both a laser and a separate high-speed modulator. However, direct modulation is characterized by significant nonlinearity in the conversion of drive current to optical intensity. We will show how this effect can be mitigated through the use of novel quadrature amplitude modulation constellations in a fully-digital implementation. Finally, we will discuss the impacts of noise and non-ideal detection in an interferometric imaging system based on the concept of phase-sensitive spectral-domain optical coherence tomography. We will analyze the impacts of noise and digital processing on the sensitivity of such a system in measuring sub-nanometer features.

Keywords: Electrical Engineering.
Advisor: Solgaard Olav primary advisor. Thesis advisor
Lyubomirsky Ilya advisor. Thesis advisor
Özgür Ayfer advisor. Thesis advisor
Mistresses, Maids, and Maternalism: Representations of Gendered Cross-Class Relationships in Victorian British Writing, 1834-1901

This interdisciplinary thesis combines sociological theory, critical methods, and digital humanities methods, taking a unique approach to investigating the cross-class relationships between middle- and working-class women in Victorian Britain. It focuses on one of the few situations in which there was sustained contact between the two groups of women—within the middle-class home as mistresses or servants. The historical relationships between the women are analyzed using sociological theories, particularly the concept of maternalism. Moreover, due to the circular relationship between printed writing and society, an investigation of mistress/maid representations in two different types of Victorian writing—domestic how-to manuals and novels—serves to provide a broader perspective on these invisible relationships, the social forces that influenced them, and the ideology surrounding them within Victorian society.

Keywords:  Department of English
 Department of Sociology
Department of English
Department of Sociology
maternalism
Victorian novels
Victorian manuals
digital humanities
Victorian Britain
Victorian British writing
Thesis
Advisor: Algee-Hewitt Mark
Ridgeway Cecilia
Moretti Franco
Mixed signals [electronic resource] : negotiating multiracial identity in high school contexts

This study investigates the ways in which mixed-race adolescents racially identify in our current racial climate, the relationships between racial identity and important life outcomes for this sample, and how the experience of schooling can be an important source of information in the development of a racial identity. Using a mixed-methods design, two types of analysis were employed. Statistical analysis was used on survey data revealing border racial identities are an overwhelmingly popular racial identity choice, regardless of participants' high schools' racial demographics or racial climate. This analysis also supports research with monoracially-identified samples that posits racial private regard is positively associated with social-psychological well-being and positive academic outcomes. Interview analysis supports the popularity of border identities, but as one of many shifting ethnic and racial identities employed for various reasons and with varying levels of agency. Interviews also reveal the ways in which high schools are places where mixed-race youth both endure microaggressions and seek out opportunities for ethnic racial socialization and understanding. Recommendations for further research and implications for practice are discussed.

Keywords: Education.
Advisor: LaFromboise Teresa Davis primary advisor. Thesis advisor
Carter Prudence L.
Elam Michele advisor. Thesis advisor
Nasir Na'ilah Suad
Mixed-initiative natural language translation [electronic resource]

There are two classical applications of the automatic translation of natural language. Assimilation is translation when a gist of the meaning is sufficient, and speed and convenience are prioritized. Dissemination is translation with the intent to communicate, so there is usually a predefined quality threshold. The most common assimilation scenario is cross-lingual web browsing, where fully automatic machine translation (MT) best satisfies the speed and convenience requirements. Dissemination is the setting for professional translators, who produce translations with the intent to communicate. MT output does not yet come with quality guarantees, so it is best incorporated as an assistive technology in this setting. This dissertation proposes a mixed-initiative approach to translation for the dissemination scenario. In a mixed-initiative system, human users and intelligent machine agents collaborate to complete some task. The central question is how to design an efficient human/machine interface. By efficient we mean that human productivity should be enhanced, and the machine should be able to self-correct its model by observing human interactions. We separate human productivity into two measurable components: translation time and quality. We first compare unaided translation to post-editing, the simplest form of machine assistance. Human translators manipulate machine output to arrive at a final translation. We find that simple post-editing decisively improves translation along both coordinates, a result that motivates more advanced machine assistance. However, it is widely observed in prior work that users regard post-editing as a tedious task. The main contribution of this dissertation is therefore a more interactive mode of machine assistance that can improve both productivity and the user experience. We present Predictive Translation Memory (PTM), a new interactive, mixed-initiative translation system. The machine suggests future translations based on previous interactions. For example, if the user has typed part of a translation for a given input sentence, PTM can propose a completion. We also show how PTM can self-correct its model via incremental machine learning. A human evaluation shows that PTM helps translators produce higher quality translations than post-editing when baseline MT quality is high. This is the desired result for dissemination. The translators are slightly slower, but we observe a significant learning curve, suggesting practice may close the time gap. In addition, PTM enables better translation model adaptation than post-editing. We describe novel machine learning techniques that result in significant reductions in human Translation Edit Rate (HTER), which is an interpretable measure of human effort. Our results suggest that adaptation could amplify time and quality gains by shifting the balance of routinizable work toward the machine agent.

Advisor: Heer Jeffrey Michael
Manning Christopher D. primary advisor. Thesis advisor
DeNero John advisor. Thesis advisor
Jurafsky Dan
Mobile visual search with text and image features [electronic resource]

Visual text information is a descriptive part of many images that has been largely neglected when performing mobile visual search (MVS). In previous methods, visual text information is treated the same as any other parts of the image and is typically represented inefficiently. In this dissertation, a new way of using visual text information for MVS is presented. To use visual text information more directly, a word patch descriptor based on image gradients in a text box is developed. The word patch descriptor can be used for large scale word patch matching, and achieves a word patch matching performance that is better than the state-of-the-art image feature-based approaches. The newly developed word patch descriptor is called the word histogram of oriented gradients (Word-HOG). An image retrieval system that uses the Word-HOG descriptor for retrieving images from databases is also developed. Text retrieval tf-idf inspired scoring methods are developed for the image retrieval system. Furthermore, a random sampling-based method is used to reduce the database. The image retrieval system achieves comparable performance to state-of-the-art image feature-based retrieval systems for images of book covers, and performs better than state-of-the-art text-based retrieval systems for images of book pages. Lastly, a lossy compression method is developed for the Word-HOG descriptor and is used with the Word-HOG-based image retrieval system to construct an MVS system. The system achieves more than 10-to-1 query size reduction for images of book covers while achieving more than 16-to-1 query size reduction for images of book pages.

Keywords: Electrical Engineering.
Advisor: Girod Bernd primary advisor. Thesis advisor
Gray Robert M.
Grzeszczuk Radek
Modalities of the long take in the era of late socialism [electronic resource] : Miklós Jancsó, Sergei Parajanov, Andrei Tarkovsky (1956-1986)

In the years between 1935 and 1975, a tangible transformation takes place in certain films of the Soviet Union and Eastern Bloc. What was once the nationally-venerated cinema of rapid-fire montage under directors such as Sergei Eisenstein and Dziga Vertov becomes the slow, single-take study of individuals and their environments. At the same time, a parallel progression of the history of the Soviet Union and the countries comprising the Eastern Bloc occurs. With the death of Lenin comes the waning hopes of world-wide revolution, the rise of Stalinism and its monumental betrayal of the Soviet People, and social and economic woes as the Soviet Union attempts and fails to integrate itself into a capitalist world system under Brezhnev. The overtly-didactic essence of montage cinema, then, makes way for its obverse: narrative and political ambiguity introduced by the long take, and viewers who must fend for themselves. This dissertation examines three filmmakers whose employment of the long take -- the realist aesthetic par excellence -- both assists and complicates our understanding of the rich historical contexts from which they emerge. This comparative analysis of the work of Miklós Jancsó, Andrei Tarkovsky, and Sergei Parajanov situates the long take at its core and will reveal the multiple ways the device as trope is used to articulate the emerging, post-Stalinist subject, the ambiguous space of criticism, and the illusion of revolution as the antidote to the horrors of Stalinism.

Keywords: Art and Art History.
Advisor: Levi Pavle primary advisor. Thesis advisor
Bukatman Scott
Skakov Nariman
Wolf Bryan Jay advisor. Thesis advisor
Modeling geological CO2 sequestration [electronic resource] : translations across spatial scales and advancements in nonlinear Newton solver

Characterization of formation heterogeneity is the first step for constructing geological models that are used in simulating subsurface flow migration, such as CO2 geological storage and oil/gas recovery. Technologies such as seismic survey, well logging, and core analysis reveal the formation heterogeneity at different scales. Due to the computational limitations on model construction and flow simulation, the gridblock size of a geological model is usually much larger than a core. The common industry practice is to assign core-scale properties directly to a geological model gridblock. The sub-grid- and sub-core-scale heterogeneities are neglected. The objective of this work is two-fold. First, we demonstrate that these small-scale heterogeneities can influence large-scale CO2 migration during geological storage. Significant modeling error may occur if these heterogeneities are not accounted for properly. Second, we improve the nonlinear convergence performance of numerical simulation, which is a crucial tool for translating small-scale physics in large-scale modeling and for uncertainty quantifications during the scale-up. A new Newton solver is developed, which converges quickly by avoiding the oscillations and overshoots that are often encountered in traditional solvers.

Keywords: Energy Resources Engineering.
Advisor: Benson Sally primary advisor. Thesis advisor
Tchelepi Hamdi primary advisor. Thesis advisor
Kitanidis P. K. (Peter K.) advisor. Thesis advisor
Modeling networks with auxiliary information [electronic resource]

Networks provide a powerful tool for representing social, technological, and biological systems. The study of networks has focused on developing models that either analytically show the emergence of global structural properties in networks or statistically perform inference tasks, such as link prediction, on given network data. This thesis presents a model of networks that not only gives rise to realistic networks with the global structural properties but also permits statistical inference for given network data. Under the proposed model, we prove many structural properties commonly found in real-world networks, such as heavy-tailed degree distributions and small diameters. We also develop a statistical inference algorithm that fits the model to given network data and represents common linking patterns through our model. A network is often associated with auxiliary information, such as node features or temporal information about node and link creations and deletions. This thesis also proposes models of networks with such auxiliary information so that the models capture the relationships between given network links and the auxiliary information. In the second part of the thesis, we propose a model that allows for relationships between given node features and network links. We develop a fitting algorithm that identifies which node features are relevant to network links and how the node features affect the formation of the links. By fitting our model to given network links and node features, our model improves performance for various prediction tasks compared to baseline models. Finally, we develop a model for dynamic networks by considering two notions of dynamics: the birth and death of each group of nodes, and each individual node's behavior of joining or leaving some node groups over time. By embedding these two dynamics into the model, we can achieve the interpretable representation of network dynamics as well as the predictive power of inferring missing links or forecasting future networks.

Keywords: Electrical Engineering.
Advisor: Leskovec Jurij primary advisor. Thesis advisor
Garcia-Molina Hector advisor. Thesis advisor
Montanari Andrea advisor. Thesis advisor
Owen Art B. advisor. Thesis advisor
Modeling noncanonical RNA 3D structures at atomic resolution under the Rosetta framework [electronic resource]

Structured non-coding RNAs play key roles in fundamental cellular processes, but determining their three-dimensional structure remains challenging. In this dissertation, I investigate the feasibility of accurate and consistent de novo modeling of RNA 3D structures at atomic resolution under the Rosetta molecular modeling framework. In the first part, I present a novel RNA structure prediction method called Stepwise Assembly. This method deterministically enumerates a low-energy subspace of the RNA's available conformations through recursively constructing well-packed atomic-detail models in small steps. Stepwise Assembly is shown to systematically outperform existing Monte Carlo and knowledge-based methods for RNA 3D structure prediction. In the second part, I then demonstrate how Rosetta RNA de novo modeling can be combined with non-exchangeable 1H NMR chemical shift data to produce high-resolution RNA structures, without the use of other NMR measurements. The resulting method is rigorously validated on 23 RNA motifs, including 11 blind tests obtained from five leading labs in the RNA NMR community.

Advisor: Das Rhiju
Harbury Pehr advisor. Thesis advisor
Pande Vijay advisor. Thesis advisor
Modeling sediment transport in San Francisco Bay [electronic resource]

The long-term evolution of shallow intertidal zones is of particular interest in light of efforts to restore coastal marshes. Factors that affect that rate of accretion or erosion of a marsh include current speeds, wind waves, tides and sediment load. These forcings change with time and vary on different time scales, and for any particular marsh the importance of each forcing may be different. Observations indicate that shallow intertidal basins tend to be characterized by a bimodal distribution of water depths into higher marshplain and lower mudflats. For shallow intertidal marshes, wind waves and tidal currents would both affect the deposition and erosion of sediments. It is hypothesized that for a shallow intertidal marsh with significant wind effects, wind waves will cause increased turbulence that enhances resuspension of sediment, leading to lower mudflats rather than higher marshplains. In this project, an attempt is made to study the factors that affect sediment deposition and resuspension, and the variability of these factors with time. Field data was collected for two weeks at a tidal wetlands restoration site, the Sonoma Baylands, California. Two locations within the field site with different wind fetches are compared to show the impact of wind on turbidity. At each site, wind speed, current velocity, wave, and turbidity data was collected. Turbidity is used as a proxy for suspended sediment concentration. Relative wave height and wave shear stress were found to be most correlated with turbidity. At the site with shorter fetch, current shear stress was almost as important as wave shear stress, but it was not significantly correlated at the site with longer fetch and larger waves. The importance of wind waves for sediment will help develop understanding of the mechanisms and factors affecting the transition of a shallow coastal region into either a marshplain accreting to mean high-high water level, or eroding into mudflat. The results of this study will be useful in determining the importance of wind waves on sedimentation, thus helping in developing strategies for restoring or protecting tidal marshes. To further study the process of sediment transport in San Francisco Bay, a three-dimensional coupled hydrodynamic, wind wave and mud suspension model SUNTANS was developed. The model was calibrated to existing meteorological, current, salinity, wave and sediment conditions. The model was found to be in general agreement with existing patterns of salinity, wave and sediment distribution. Higher sediment concentrations were generally found in locations of higher wind, shallow depths, complicated bathymetry, and/or down wind locations, in line with the established understanding of wind-induced sediment resuspension together with current induced erosion and advective transport.

Keywords: Civil and Environmental Engineering.
Advisor: Koseff Jeffrey Russell advisor. Thesis advisor