VictorJuiz/thesis huggingface dataset:
Migrant and Border Subjects in Late Choson Korea

This thesis explores the changing approach of the Chosŏn state to subjects with foreign lineages in the period between the Imjin War (1592-98) and the early nineteenth century. Chosŏn Korea underwent considerable upheaval during the Imjin War and the wars of the Ming-Qing transition. Many Jurchen subjects of the Chosŏn court were forced from their homes in the Tumen Valley into the banner armies of the rising Qing state, with only a remnant persisting in Chosŏn. Additionally, large numbers of Ming Chinese entered Chosŏn either with the Ming army or as refugees from war in Liaodong. Initially, the Chosŏn state responded to its Jurchen and Ming Chinese subjects primarily through pragmatic concern about the loyalty of these subjects to the Chosŏn and the burden they imposed on the agricultural economy. As a result, the Chosŏn court welcomed and even defended the Jurchen as established Chosŏn subjects but was cautious of the more alien Ming deserters and refugees. Ming migrant status did not improve during the remainder of the seventeenth century. Ming Chinese lineages were considered, along with Jurchen and Japanese, within the same invidious submitting foreigner tax category. During the same period fraudulent Ming migrants became a focus for sedition among non-elites. The eighteenth century rise of Ming Loyalist ritualism transformed the response of the Chosŏn court to such foreign lineages as Ming migrant lineages were encouraged to participate in court-sponsored Ming loyalist rituals. Along with this ritual participation Ming migrant status was transformed from that of submitting foreigners to that of imperial subjects, while Jurchen and Japanese lineages disappeared. At the same time, hagiographic biographies were written of the original Ming Chinese refugees which praised them for coming to Chosŏn because of Neo-Confucian loyalty to the Ming. The Chosŏn state responded to foreign lineages according to changing circumstances. Neo-Confucian ritualism only played a role in response to Ming lineages in the eighteenth century when earlier concerns about disloyalty and social disruption had largely passed.

Keywords: Korea
Choson
Neo-Confucianism
Ming
Jurchen
Migration
Lineage
Ritual
Qing
Manchu
Advisor: Schmid, Andre
Neural Mechanisms of Temporomandibular Joint and Masticatory Muscle Pain

The underlying nociceptive mechanisms in temporomandibular joint (TMJ) and masticatory muscles in many pain conditions are still unclear, largely due to the limited study of peripheral and central neural mechanisms affecting craniofacial musculoskeletal tissues. This study provided evidence in support of Hypothesis 1: Peripheral glutamatergic and capsaicin-sensitive mechanisms modulate the properties of primary afferents and brainstem neurons processing deep craniofacial nociceptive information. Effects of glutamate and capsaicin injected into the receptive field of deep craniofacial nociceptive afferents or TMJ of TMJ-responsive nociceptive neurons in trigeminal subnucleus caudalis/upper cervical cord (Vc/UCC) were studied in halothane-anesthetized rats. When injected alone, glutamate and capsaicin activated and induced peripheral sensitization in many afferents. Following glutamate injection, capsaicin-evoked activity was greater than that evoked by capsaicin alone, whereas following capsaicin injection, glutamate-evoked responses were similar to those of glutamate alone. When injected alone, glutamate and capsaicin also activated and induced central sensitization in most Vc/UCC neurons. Following glutamate injection, capsaicin evoked greater activity and less sensitization compared with capsaicin alone, whereas following capsaicin, glutamate was less effective in activating and sensitizing most Vc/UCC neurons. This apparent desensitizing effect of capsaicin on glutamate-evoked excitability of Vc/UCC neurons contrasts with the lack of capsaicin-induced modulation of glutamate-evoked afferent excitability, suggesting that peripheral and central sensitization may be differentially involved in the nociceptive effects of glutamate and capsaicin applied to deep craniofacial tissues. Further evidence of glutamate-capsaicin interactions was documented in the attenuation by TMJ pre-injection of glutamate receptor antagonists of jaw muscle activity reflexly evoked by TMJ injection of capsaicin. Moreover, additional findings support Hypothesis 2: Surgical cutaneous incision modulates the properties of brainstem neurons processing deep craniofacial nociceptive information. TMJ-responsive nociceptive Vc/UCC neurons could be activated by surgical incision of the skin overlying the TMJ and this incision-induced afferent barrage caused nociceptive neurons to be temporarily refractory to further capsaicin-induced central sensitization. These novel findings suggest that peripheral glutamate and capsaicin receptor mechanisms as well as surgical cutaneous incision may be involved in the nociceptive processing of deep craniofacial afferent inputs and may interact to modulate both activation as well as sensitization evoked from these tissues.

Keywords: excitatory amino acid
TRPV1
glutamate
capsaicin
incision
trigeminal
pre-emptive analgesia
Advisor: Hu, James W.
Sessle, Barry John
Behavioural Model Fusion

In large-scale model-based development, developers periodically need to combine collections of interrelated models. These models may capture different features of a system, describe alternative perspectives on a single feature, or express ways in which different features alter one another's structure or behaviour. We refer to the process of combining a set of interrelated models as "model fusion". A number of factors make model fusion complicated. Models may overlap, in that they refer to the same concepts, but these concepts may be presented differently in each model, and the models may contradict one another. Models may describe independent system components, but the components may interact, potentially causing undesirable side effects. Finally, models may cross-cut, modifying one another in ways that violate their syntactic or semantic properties. In this thesis, we study three instances of the fusion problem for "behavioural models", motivated by real-world applications. The first problem is combining "partial" models of a single feature with the goal of creating a more complete description of that feature. The second problem is maintenance of "variant" specifications of individual features. The goal here is to combine the variants while preserving their points of difference (i.e., variabilities). The third problem is analysis of interactions between models describing "different" features. Specifically, given a set of features, the goal is to construct a composition such that undesirable interactions are absent. We provide an automated tool-supported solution to each of these problems and evaluate our solutions. The main novelties of the techniques presented in this thesis are (1) preservation of semantics during the fusion process, and (2) applicability to large and evolving collections of models. These are made possible by explicit modelling of partiality, variability and regularity in behavioural models, and providing semantic-preserving notions for relating these models.

Keywords: Model Merging
Model Composition
Model Management
Behavioural Models
Refinement
Temporal Logic
Bisimulation/Simulation
State Machine
Advisor: Chechik, Marsha
Interactive Content Adaptation

Mobile devices are increasingly being used to access Web content but lack the resources for proper presentation to the user. To address this problem, content is typically customized to be more suitable for a mobile environment. Automatic customization of web content is a challenging problem because fine-grain adaptation often depends on both the relevance of individual objects on a web page, as well as the context of access (e.g., screen size of device being used, network connectivity, location, etc.). We present Usage-aware Interactive Content Adaptation, an adaptation technique that allows a user who is unsatisfied with the system’s adaptation decision to take control of the adaptation process and make changes until the content is suitably adapted for her purposes. The adaptation system learns from the user’s modifications and adjusts its prediction for future accesses by other users. With this approach, users are empowered to correct bad adaptation decisions made by the system without being overly burdened. We applied the technique in two domains: adapting the quality of images to reduce download times and save energy and bandwidth, and customizing the layout of images to improve the utilization of screen real-estate. The work was evaluated through a series of user studies, and the results show that user feedback can be effectively used to provide appropriate customizations (i) for objects with varying relevance, (ii) when context affects the users adaptation requirements, and (iii) when the same content can be used for multiple purposes by different users.

Keywords: Content Adaptation
Mobile Devices
Web
Customization
Context
Systems
Advisor: Lara, Eyal de
Acquiring and Reasoning about Variability in Goal Models

One of the most essential parts of any software requirements analysis effort is the exploration of alternative ways by which stakeholder problems can be solved. Systematic modeling and analysis of requirements variability allows better decision making during the early requirements phase and substantiates design choices pertaining to the configurability aspect of the system-to-be. This thesis proposes the use of goal models for capturing and reasoning about requirements variability. The goal models we adopt consist of AND/OR decompositions of stakeholder goals and express alternative ways by which stakeholders may wish to achieve them. By capturing goal variability using such models, we propose a shift of focus from variability of the software design, to variability of the problem that the design is intended to solve. This way, we ensure that every important variation of the problem is identified and analyzed before variations of the solution are specified. The thesis exploits opportunities that arise from this new viewpoint. Firstly, a variability-intensive goal decomposition process is proposed. The process is based on associating each high-level goal to a set of variability concerns that must be addressed through decomposition. We introduce a universal categorization of such concerns and also show how domain-specific variability concerns can be identified by annotating domain corpora. Concern-driven decomposition offers a structured way of thinking about problem variability, while systematizing its identification process. Further, an expressive LTL-based preference language is introduced to support leverage of large spaces of goal alternatives. The language allows the expression of preferences over behavioral and qualitative properties of solutions and a reasoning tool allows the identification of alternatives that satisfy these preferences. This way, individual stakeholders can get the solution that exactly fits their needs in a particular situation, through simply specifying desired high-level characteristics of these solutions. Finally, a framework for connecting alternatives at the goal level to alternative configurations of common desktop applications is presented. The framework shows how a vast number of configurations of a software application can be evaluated and ranked with respect to a small number of quality goals that are more intuitive to and comprehensible by end users.

Keywords: Software Engineering
Requirements Engineering
Advisor: Mylopoulos, John
Nogood Processing in CSPs

The constraint satisfaction problem is an NP-complete problem that provides a convenient framework for expressing many computationally hard problems. In addition, domain knowledge can be efficiently integrated into CSPs, providing a potentially exponential speedup in some cases. The CSP is closely related to the satisfiability problem and many of the techniques developed for one have been transferred to the other. However, the recent dramatic improvements in SAT solvers that result from learning clauses during search have not been transferred successfully to CSP solvers. In this thesis we propose that this failure is due to a fundamental restriction of \newtext{nogood learning, which is intended to be the analogous to clause learning in CSPs}. This restriction means that nogood learning can exhibit a superpolynomial slowdown compared to clause learning in some cases. We show that the restriction can be lifted, delivering promising results. Integration of nogood learning in a CSP solver, however, presents an additional challenge, as a large body of domain knowledge is typically encoded in the form of domain specific propagation algorithms called global constraints. Global constraints often completely eliminate the advantages of nogood learning. We demonstrate generic methods that partially alleviate the problem irrespective of the type of global constraint. We also show that more efficient methods can be integrated into specific global constraints and demonstrate the feasibility of this approach on several widely used global constraints.

Keywords: Computer Science
Constraint Satisfaction
Propositional Satisfiability
Advisor: Bacchus, Fahiem
Clause Learning, Resolution Space, and Pebbling

Currently, the most effective complete SAT solvers are based on the DPLL algorithm augmented by Clause Learning. These solvers can handle many real-world problems from application areas like verification, diagnosis, planning, and design. Clause Learning works by storing previously computed, intermediate results and then reusing them to prune the future search tree. Without Clause Learning, however, DPLL loses most of its effectiveness on real world problems. Recently there has been some work on obtaining a deeper understanding of the technique of Clause Learning. In this thesis, we contribute to the understanding of Clause Learning, and the Resolution proof system that underlies it, in a number of ways. We characterize Clause Learning as a new, intuitive Resolution refinement which we call CL. We then show that CL proofs can effectively p-simulate general Resolution. Furthermore, this result holds even for the more restrictive class of greedy, unit propagating CL proofs, which more accurately characterize Clause Learning as it is used in practice. This result is surprising and indicates that Clause Learning is significantly more powerful than was previously known. Since Clause Learning makes use of previously derived clauses, it motivates the study of Resolution space. We contribute to this area of study by proving that determining the variable space of a Resolution derivation is PSPACE-complete. The reduction also yields a surprising exponential size/space trade-off for Resolution in which an increase of just 3 units of variable space results in an exponential decrease in proofsize. This result runs counter to the intuitions of many in the SAT-solving community who have generally believed that proof-size should decrease smoothly as available space increases. In order to prove these Resolution results, we need to make use of some intuition regarding the relationship between Black-White Pebbling and Resolution. In fact, determining the complexity of Resolution variable space required us to first prove that Black-White Pebbling is PSPACE-complete. The complexity of the Black-White Pebbling Game has remained an open problem for 30 years and resisted numerous attempts to solve it. Its solution is the primary contribution of this thesis.

Keywords: Proof Complexity
Black-White Pebbling
Advisor: Pitassi, Toniann
Applications of Games to Propositional Proof Complexity

In this thesis we explore a number of ways in which combinatorial games can be used to help prove results in the area of propositional proof complexity. The results in this thesis can be divided into two sets, the first being dedicated to the study of Resolution space (memory) requirements, whereas the second is centered on formalizing the notion of `dangerous' reductions. The first group of results investigate Resolution space measures by asking questions of the form, `Given a formula F and integer k, does F have a [Type of Resolution] proof with [Type of Resource] at most k?'. We refer to this as a proof complexity resource problem, and provide comprehensive results for several forms of Resolution as well as various resources. These results include the PSPACE-Completeness of Tree Resolution clause space (and the Prover/Delayer game), the PSPACE-Completeness of Input Resolution derivation total space, and the PSPACE-Hardness of Resolution variable space. This research has theoretical as well as practical motivations: Proof complexity research has focused on the size of proofs, and Resolution space requirements are an interesting new theoretical area of study. In more practical terms, the Resolution proof system forms the underpinnings of all modern SAT-solving algorithms, including clause learning. In practice, the limiting factor on these algorithms is memory space, so there is a strong motivation for better understanding it as a resource. With the second group of results in this thesis we investigate and formalize what it means for a reduction to be `dangerous'. The area of SAT-solving necessarily employs reductions in order to translate from other domains to SAT, where the power of highly-optimized algorithms can be brought to bear. Researchers have empirically observed that it is unfortunately possible for reductions to map easy instances from the input domain to hard SAT instances. We develop a non-Hamiltonicity proof system and combine it with additional results concerning the Prover/Delayer game from the first part of this thesis as well as proof complexity results for intuitionistic logic in order to provide the first formal examples of harmful and beneficial reductions, ultimately leading to the development of a framework for studying and comparing translations from one language to another.

Keywords: Proof Complexity
Computational Complexity
Resolution Space
Automated Theorem Proving
Combinatorial Games
Advisor: Urquhart, Alasdair
Variable-aperture Photography

While modern digital cameras incorporate sophisticated engineering, in terms of their core functionality, cameras have changed remarkably little in more than a hundred years. In particular, from a given viewpoint, conventional photography essentially remains limited to manipulating a basic set of controls: exposure time, focus setting, and aperture setting. In this dissertation we present three new methods in this domain, each based on capturing multiple photos with different camera settings. In each case, we show how defocus can be exploited to achieve different goals, extending what is possible with conventional photography. These methods are closely connected, in that all rely on analyzing changes in aperture. First, we present a 3D reconstruction method especially suited for scenes with high geometric complexity, for which obtaining a detailed model is difficult using previous approaches. We show that by controlling both the focus and aperture setting, it is possible compute depth for each pixel independently. To achieve this, we introduce the "confocal constancy" property, which states that as aperture setting varies, the pixel intensity of an in-focus scene point will vary in a scene-independent way that can be predicted by prior calibration. Second, we describe a method for synthesizing photos with adjusted camera settings in post-capture, to achieve changes in exposure, focus setting, etc. from very few input photos. To do this, we capture photos with varying aperture and other settings fixed, then recover the underlying scene representation best reproducing the input. The key to the approach is our layered formulation, which handles occlusion effects but is tractable to invert. This method works with the built-in "aperture bracketing" mode found on most digital cameras. Finally, we develop a "light-efficient" method for capturing an in-focus photograph in the shortest time, or with the highest quality for a given time budget. While the standard approach involves reducing the aperture until the desired region is in-focus, we show that by "spanning" the region with multiple large-aperture photos,we can reduce the total capture time and generate the in-focus photo synthetically. Beyond more efficient capture, our method provides 3D shape at no additional cost.

Keywords: computer vision
computer graphics
computational photography
3D reconstruction
shape-from-focus
shape-from-defocus
image-based rendering
high dynamic range imaging
camera calibration
multiview stereo
optics
Advisor: Kutulakos, Kiriakos Neoklis
Interaction with Volumetric Displays

For almost 50 years, researchers have been exploring the use of stereoscopic displays for visualizing and interacting with three-dimensional (3D) data. Unfortunately, a number of unfavorable qualitative properties have impeded the wide-spread adoption of traditional 3D displays. The volumetric display, a more recent class of 3D display to emerge, possesses unique features which potentially makes it more suitable for integration into workplace, classroom, and even home environments. In this dissertation we investigate volumetric displays as an interactive platform for 3D applications. We identify the inherent affordances unique to volumetric displays, such as their true 3D display volume, 360° viewing angle, and enclosing surface. Identifying these properties exposes human factor issues which we investigate and interaction issues which we address. First, we evaluate the user’s ability perceive imagery displayed by a volumetric display. In a formal experiment, we show that depth perception can be improved, in comparison to more traditional platforms. We then perform an experiment which evaluates users’ ability to read text under 3D rotations, and present a new algorithm which optimizes text rotation when viewed my multiple users. Next, we investigate the user’s ability to select 3D imagery within the display. Results show that the dimension defining the depth of the object can constrain user performance as much as or more than the other two dimensions of the target. This leads us to explore alternative methods of selection which are less constraining to the user. We define a suite of new selection techniques, of which several are found to have significant benefits in comparison to techniques traditionally used in 3D user interfaces. Next, we describe our development of the first working interactive application, where a volumetric display is the sole device for input and display. The application presents a first glance at what the equivalent of today’s graphical user interface might be on a volumetric display. We then develop a prototype application which allows multiple users to simultaneously interact with the volumetric display. We discuss and address the core issues related to providing such a collaborative user interface, and report feedback obtained from usage sessions and expert interviews.

Keywords: Volumetric Display
3D Interaction
Advisor: Balakrishnan, Ravin