VictorJuiz/thesis huggingface dataset:
Building Operating Systems Services: An Architecture for Programmable Buildings

Commercial buildings use 73% of all electricity consumed in the United States, and numerous studies suggest that there is a significant unrealized opportunity for savings. One of the many reasons this problem persists in the face of financial incentives is that owners and operators have very poor visibility into the operation of their buildings. Making changes to operations often requires expensive consultants, and the technological capacity for change is unnecessarily limited. Our thesis is that some of these issues are not simply failures of incentives and organization but failures of technology and imagination: with a better software framework, many aspects of building operation would be improved by innovative software applications./nTo evaluate this hypothesis, we develop an architecture for implementing building applications in a flexible and portable way, called the Building Operating System Services. BOSS allows software to reliability and portably collect, process, and act on the large volumes of data present in a large building./nThe minimal elements of this architecture are hardware abstraction, data management and processing, and control design; in this thesis we present a detailed design study for each of these components and consider various tradeoffs and findings. Unlike previous systems, we directly tackle the challenges of opening the building control stack at each level, providing interfaces for programming and extensibility while considering properties like scale and fault-tolerance./nOur contributions consist of a principled factoring of functionality onto an architecture which permits the type of application we are interested in, and the implementation and evaluation of the three key components. This work has included significant real-world experience, collecting over 45,000 streams of data from a large variety of instrumentation sources in multiple buildings, and taking direct control of several test buildings for a period of time. We evaluate our approach using focused benchmarks and case studies on individual architectural components, and holistically by looking at applications built using the framework.

Advisor: Culler, David
Viaje literario con José Manuel Caballero Bonald y Fernando Quiñones. Oriente-Andalucía-Occidente: una ruta para reimaginar la Andalucía del Tardofranquismo a la Postransición

This dissertation analyzes the prose of José Manuel Caballero Bonald and Fernando Quiñones, and the cinema from Late-Francoism to Post-Transition, paying especial attention to the flamenco films by Carlos Saura. Their shared historical Andalusian background provides an opportunity to examine the shift from Francoist centralism to the quasi-federalism of Spain's "Autonomous Communities" (la España de las Autonomías), as well as their notion of Andalusian identity within the framework of Andalusia as a newly minted Autonomous Community since 1981. Drawing on anthropology, Colonial Studies, history, and social theory, the study adopts an interdisciplinary approach as it examines the issue of Andalusian identity from the above-mentioned perspectives using a diverse corpus of texts from literature, film and the performing arts. The first two chapters focus on the rise of Andalusia as an Autonomía, and Caballero Bonald and Quiñones' attempt to purge Andalusia's stereotypical image. They review the history of the colonization of the Iberian Peninsula by the Phoenicians and the Arabs, as well as the arrival of Gypsies during the Middle Ages -which contributed to the consolidation of flamenco- and the ensuing cultural mix that was the basis for Caballero Bonald and Quiñones' concept of Andalusian identity. The third chapter analyzes the symbols they chose to represent their identity: the bull, the horse, and wine. The last two chapters explore the role of Andalusians as colonizers of the New World, who are in turn "colonized" as certain components of Latin American cultural production make their way into Andalusian aesthetics with an emphasis in the (Neo)Baroque and the "marvelous real" (real maravilloso). I find that, in the given context, both Caballero Bonald and Quiñones reflect on their identity, concluding that its particular essence is based on both mestizaje -the intermixing of Oriental, European and American cultures-and the dual status of the Iberian Peninsula as both colonizer and colonized.

Advisor: Iarocci, Michael
Modeling neural representation using statistical features of natural scenes

A primary focus of neuroscience is understanding how information about the world is encoded in the activity of neurons. The classic approach to studying neural representation is to observe how activity in a neural system is modulated when presented with stimuli that vary along a specific, hypothesis-driven dimension (e.g. luminance, contrast, orientation, spatial frequency). This approach offers straight-forward interpretation and has allowed neuroscientists to develop computational models of the stimulus-response function for neurons in early processing stages of the visual system. However, the interpretations of these studies often do not generalize to other stimuli such as natural images, and the corresponding computational models often fail to explain later processing stages where the stimulus-response function is strikingly nonlinear. What is needed is an alternative approach that can a) inform new hypotheses without relying on the intuitions of the experimenter, b) generate tractable and interpretable nonlinear models of neural function based on these hypotheses, and c) directly assess model accuracy at predicting neural function under natural conditions. In this dissertation I propose a simple but powerful framework that uses statistical feature learning to automatically derive potential forms of neural representation and generates predictive and testable models of neural function based on these potential representations. The framework is general and can potentially be applied to data acquired using any physiological measurement technique (e.g. neurophysiology, neuroimaging, behavioral) in order to model neural representation throughout the brain. I demonstrate the potential of the proposed framework by first modeling the neural representation of image structure in early cortical stages of the macaque visual system (areas V1 and V2). I then apply the framework to investigate high-level scene processing in the human visual system. In both case studies, I am able to objectively derive accurate and interpretable nonlinear models of neural representation. In each study, I am also able to replicate and extend findings from a multitude of classic neurophysiology and neuroimaging studies using a single, simple experiment based on natural visual stimuli.

Advisor: Gallant, Jack L
Cloud-based Methods and Architectures for Robot Grasping

The Cloud has the potential to enhance a broad range of robotics and automation systems. Cloud Robotics and Automation systems can be broadly defined as follows: Any robotic or automation system that relies on either data or code from a network to support its operation, i.e., where not all sensing, computation, and memory is integrated into a single standalone system. We identify four potential benefits of Cloud Robotics and Automation: 1) Big Data: access to remote libraries of images, maps, trajectories, and object data, 2) Cloud Computing: access to parallel grid computing on demand for statistical analysis, learning, and motion planning, 3) Collective Robot Learning: robots sharing trajectories, control policies, and outcomes, and 4) Human computation: using crowdsourcing access to remote human expertise for analyzing images, classification, learning, and error recovery./nWe present four Cloud Robotics and Automation systems in this dissertation. First, we develop a system for Cloud-based grasping of 2D polygonal objects with uncertainty in shape using an analytic conservative estimate of the probability of force closure. Second, we develop a system for Cloud-based grasping of 2D polygonal objects with uncertainty in pose, using a quasi-static simulation that is less conservative than the approach for the first system. These two systems demonstrate the usefulness of Cloud-based parallelism for handling uncertainty. Third, we develop a system for recognizing and grasping household objects using the Google Object Recognition Engine as a web service and using Cloud storage of object and grasp information. Finally, we develop a system for providing algorithms as web services and integrating datasets with these services. These systems advance the understanding of the benefits the Cloud can provide for Robotics and Automation.

Advisor: Goldberg, Ken
Hedrick, Karl
The Professional Development of Teachers of English Learners

This study investigates how middle school teachers who engaged in a teacher professional development program that focuses on the development of academic literacy for English learners, implemented the program's instructional tools in their classroom instruction. This research sheds light on teachers' understanding of the professional development and their subsequent decision-making for appropriating, or not appropriating, new instructional tools and practices from the program as they enacted their literacy goals for student learning in English language arts and English language development classrooms./nThis study contributes to the understanding of the situated nature of teacher professional development and teachers' implementation efforts. This research offers an analysis of the tensions that emerged between the various discourses about teaching and learning for three eighth grade teachers' perceptions of the professional development. The findings suggest that the discourses of standardized testing, accountability for student achievement, and classroom participation influenced how teachers negotiated and prioritized competing goals for student learning. Further, this research examines each of the three case study teachers' implementation in their respective classrooms, two in regular eighth-grade English language arts classrooms with English learners and one in a specialized English language development course with only English learners. The case study teachers and classrooms afforded the examination of teachers' implementation in various instructional settings with English learners. The findings from the case studies suggest that teachers negotiated their implementation of the professional development program in a variety of ways. The analysis demonstrates that when the teachers enacted the program's instructional tools and practices, they appropriated them by making modifications that were aligned to their goals for students' literacy. One case study teacher uses both compliance and the power to reject the professional development in order to maintain established teaching practices. The second case study teacher highlights the roles of compliance, resistance, and rejection following unsuccessful implementations with her students. The third case study teacher points to an implementation that integrates the professional development among other instructional tools and practices but also resists and rejects aspects of the professional development. The analysis of the case study teachers' implementation and appropriation of the professional development also highlights the various ways in which teachers make sense of how new instructional tools and practices support their goals for teaching and student learning.

Advisor: Freedman, Sarah W
The Photographic World Picture

This dissertation examines photography's relationship to beliefs in universal order, and the emergence of a photographic "world picture" in art. It argues that the concept of a "taken" picture arises with empirical scientific methods in the early eighteenth century, and ties the "taken" pictures of four artists in the early modern and contemporary eras to the emergence of period worldviews: Canaletto's paintings to Newtonian mechanics, Bernd and Hilla Becher's typologies to structuralism, and Andreas Gursky's large-scale digital photographs to globalization./nChapter 1 uncovers the "taken" picture's origins as a commodity in Canaletto's paintings of 1730s Venice, and shows how they were made to seem to British tourists like observations through Isaac Newton's eyes--cut from a mechanically homogenous world. Canaletto's paintings, executed through the lens of a camera obscura, "captured" moments of space and time by analogizing the artistic act of "taking views" to the scientific act of "taking samples." Chapter 2 follows Canaletto to London, where the artist creates the first view paintings of an endless built world. The chapter shows how these massive cityscapes evoke a cultural sublime before the advent of sublime paintings of nature. These paintings anticipate the form and scale of Andreas Gursky's digital photographs of globalization by more than two centuries and also presage modern skepticism of Enlightenment humanism: how, they ask, can a human observer see himself as part of universal, deterministic system? Chapter 3 shows how Bernd and Hilla Becher's typologies of industrial buildings photographically answered that question when they were adopted into the conceptual art world of the late 1960s and 1970s. The chapter reveals that the Bechers' pictorial formula helped viewers experience their own faculties being as mechanically determined as those of the industrial buildings--just as structuralism and computational cognitive science were then predicting. Finally, in Chapter 4, I demonstrate how Andreas Gursky turned the intangible concept of "globalization" into a photographic experience through digital imaging technology. Gursky arrived at a "photographic world picture" by seeming to have taken a photograph of a systematic fallout to our individual intentions, spread over an indefinite landscape. In doing so, he discovered what Canaletto was looking for in London--a place in the built landscape from which global logic could be observed. The four chapters of this dissertation show how photography gave visual form to notions of universal structural order.

Advisor: Clark, Timothy J
Silverman, Kaja
Students' Understandings of Arithmetic Generalizations

This study examines fourth graders' understandings of arithmetic generalizations, the general properties of arithmetic that hold true for all numbers. Its focus is on three types of generalizations: (a) direction of change (e.g., addition of positive numbers increases the numerical value, while subtraction of positive numbers decreases the numerical value); (b) identity (e.g., the addition or subtraction of 0 to any number leaves its value unchanged); and (c) relationship between operations (e.g., addition and subtraction are inverse operations). Using a between subjects design, two interview studies were conducted to investigate the character of children's understandings and to understand how students' production of generalizations varied across different tasks (e.g., I am thinking about a number. If I multiply that number by 5 and then divide by 5, what will happen to my number?). Study 1 (n=24) focused on students' additive thinking in the context of addition and subtraction tasks, while Study 2 (n=24) focused on multiplicative thinking in the context of multiplication and division tasks./nIn both studies, qualitative analyses of the video data revealed four levels in student thinking, levels that show a spectrum of increasing generality with which students treat arithmetic operations. At Levels 1 and 2, students rely on specific instances and substitution of values. At Levels 3 and 4 (advanced generalizations), students do not rely on any examples and make generalizations about the arithmetic operations. Further quantitative analyses revealed that student thinking was not always consistent and that students' production of advanced generalizations was affected by generalization type and domain type. In both studies, the identity tasks prompted the most advanced generalizations, while the relationship between operations tasks elicited the least advanced generalizations from students. Similarly, children were more likely to produce an advanced generalization in the additive domain than in the multiplicative domain. Although the multiplicative tasks may have been more challenging for students, the character of students' thinking and the difficulty of the tasks in relation to one another were similar across both domains. These parallel findings across the studies indicate that additive and multiplicative generalizations may involve similar developmental progressions./nThis dissertation provides insight into a developmental model about children's construction of arithmetic generalizations. First, the four levels of generality describe qualitative shifts in student thinking and, second, these findings indicate that the development of students' understandings of arithmetic generalizations may be heterogeneous across a range of generalizations. This work can contribute to teachers' knowledge for teaching and inform the design of a developmentally appropriate instructional sequence.

Advisor: Saxe, Geoffrey B
Schoenfeld, Alan
Selectively De-animating and Stabilizing Videos

This thesis presents three systems for editing the motion of videos. First, selectively de-animating videos seeks to remove the large-scale motions of one or more objects so that other motions are easier to see. The user draws strokes to indicate the regions that should be immobilized, and our algorithm warps the video to remove large-scale motion in regions while leaving finer-scale, relative motions intact. We then use a graph-cut-based optimization to composite the warped video with still frames from the input video to remove unwanted background motion. Our technique enables applications such as clearer motion visualization, simpler creation of artistic cinemagraphs, and new ways to edit appearance and motion paths in video. Second, we design a fully automatic system to create portrait cinemagraphs by tracking facial features and de-animating the video with respect to the face and torso. We then generate compositing weights automatically to create the final cinemagraph portraits./nThird, we present a user-assisted video stabilization algorithm that is able to stabilize challenging videos when state-of-the-art automatic algorithms fail to generate a satisfactory result. Our system introduces two new modes of interaction that allow the user to improve an unsatisfactory automatically stabilized video. First, we cluster tracks and visualize them on the warped video. The user ensures that appropriate tracks are selected by clicking on track clusters to include or exclude them to guide the stabilization. Second, the user can directly specify how regions in the output video should look by drawing quadrilaterals to select and deform parts of the frame. Our algorithm then computes a stabilized video using the user-selected tracks, while respecting the user-modified regions.

Advisor: Ramamoorthi, Ravi
Dissecting the functional and morphological contributions of the glucocorticoid receptor gene in neural progenitor cells of the hippocampus

Stress hormones are known as one of the strongest and most ecologically relevant mediators of adult neurogenesis. A lingering question in adult neurogenesis is whether these hormones, known as corticosteroids (cortisol in humans, corticosterone in rodents), act directly on neural progenitor cells (NPCs), or indirectly through secreted factors or changes in network activity. Additionally, the functional contributions of this impact are largely speculative. To address these unknowns, we generated a transgenic mouse model whose glucocorticoid receptors (GRs) could be inducibly inactivated specifically in NPCs. GRs are the main target that corticosteroids bind to when elevated during stress. We investigated the effect of this cell-specific GR knockout model on hippocampal survival and differentiation and found them to be similarly affected by chronic corticosterone treatment compared to controls. This implies that corticosterone-suppressed neurogenesis and its impact on morphology is indirect, and GR in other cells may be mediating the effects. Furthermore, mice with GR inactivation in newborn neurons behaved similarly to controls in all tasks observed under basal levels of corticosterone. When mice were chronically treated with corticosterone, however, controls exhibited an anxious phenotype in novelty-suppressed feeding (NSF), light/dark box, and elevated Omaze, whereas transgenic mice behaved like untreated control groups in all anxiety measures except latency to feed in NSF. Neither corticosterone nor inactivation of GR in adult-born neurons altered depression-like behaviors in the forced swim test, nor percent freezing in contextual fear discrimination. Lastly, we found that corticosterone increased the rate of learning in 1-trial contextual fear conditioning, an effect not mediated by reducing GR signaling in the neurogenic pool. These results highlight the functional contributions of adult neurogenesis as well as how their GRs mediate anxiety-relevant behaviors irrespective of suppressed neurogenesis.

Advisor: Kaufer, Daniela
Clusters and Features from Combinatorial Stochastic Processes

Clustering involves placing entities into mutually exclusive categories. We wish to relax the requirement of mutual exclusivity, allowing objects to belong simultaneously to multiple classes, a formulation that we refer to as "feature allocation." The first step is a theoretical one. In the case of clustering the class of probability distributions over exchangeable partitions of a dataset has been characterized (via exchangeable partition probability functions and the Kingman paintbox). These characterizations support an elegant nonparametric Bayesian framework for clustering in which the number of clusters is not assumed to be known a priori. We establish an analogous characterization for feature allocation; we define notions of "exchangeable feature probability functions" and "feature paintboxes" that lead to a Bayesian framework that does not require the number of features to be fixed a priori. We focus on particular models within this framework that are both practical for inference and provide desirable modeling properties. And we explore a further generalization to feature allocations where objects may exhibit any non-negative integer number of features, or traits./nThe second step is a computational one. Rather than appealing to Markov chain Monte Carlo for Bayesian inference, we develop a method to transform Bayesian methods for feature allocation (and other latent structure problems) into optimization problems with objective functions analogous to K-means in the clustering setting. These yield approximations to Bayesian inference that are scalable to large inference problems.

Advisor: Jordan, Michael I