VictorJuiz/thesis huggingface dataset:
Data-driven instructional leadership and the necessity of relational trust [electronic resource] : a case study in principal leadership

This case study of a small high school demonstrates the effects of principal leadership dispositions and activities on relational trust within a school community and especially between the principal and school faculty. Through an analysis of evidence from site observations and interviews of classroom teachers and site administrators over three school years, the author concludes that the school-based outcomes of data-driven instructional leadership correlate with extant levels of relational trust among faculty, and correlate with the principal's approach to collecting and employing data during the process of school reform. Teacher reports of instructional reform activities as well as student standardized test outcomes and teacher retention data all support the conclusion that teachers are more engaged in professional improvement, work longer days and weeks voluntarily, and adopt a "whatever it takes attitude" towards school reform when led by a principal who builds relational trust by collecting and using data to support teacher professional development, communicate respect for teachers and augment teacher voice and inclusion in site-based decision-making.

Keywords: Education.
Advisor: Darling-Hammond Linda
Lieberman Ann
Lotan Rachel A. advisor. Thesis advisor
McDermott Ray (Raymond Patrick)
Data-driven tools for scene modeling [electronic resource]

Detailed digital environments are crucial to achieving a sense of immersion in video games, virtual worlds, and cinema. The modeling tools currently used to create these environments rely heavily on single-object modeling: designers must repeatedly search for, place, align, and scale each new object in a scene that may contain thousands of models. This style of scene design is enabled by the large collections of 3D models which are becoming available on the web. While these databases make it possible for designers to incorporate existing content into new scenes, the process can be slow and tedious: the rate at which we can envision new content greatly exceeds the rate at which we can realize these imagined constructs as digital creations. In this dissertation, we aim to alleviate this bottleneck by developing tools that accelerate the modeling of 3D scenes. We rely upon a data-driven approach, where we learn common scene modeling design patterns from examples of 3D environments. We show which properties of scene databases such as Google 3D Warehouse are most important for data-driven tasks, and how to transform existing scene databases into a form that is amenable to pattern learning. We also describe a custom scene modeling program which serves as a testbed for the modeling tools we develop, and which we use to create a curated corpus of scenes that enable the development of powerful modeling tools. Our tools require the ability to compare arrangements of objects. We present several techniques to do so, including kernel density estimation and graph kernels, and show how these approaches can be applied to produce practical modeling tools. We use this machinery to support basic modeling operations such as searching for or orienting single models. We show how to use a corpus of 3D scenes to automatically categorizing and aligning collections of objects by group objects into contextual categories. Finally, we combine these contextual categories and our arrangement comparison algorithm to enable example-based 3D scene synthesis, where the artist provides a small number of examples and we generate a diverse and plausible set of similar scenes. All of the methods we develop use a data-driven approach in order to enable the rapid construction of large virtual environments without the need for an artist to try and specify the \rules of design" for each possible domain.

Advisor: Hanrahan P. M. (Patrick Matthew) primary advisor. Thesis advisor
Klemmer Scott advisor. Thesis advisor
Tversky Barbara advisor. Thesis advisor
Decentralized control and the analysis of electrical distribution systems [electronic resource]

This thesis studies the design and analysis of decentralized control over stochastic nonlinear systems. Different from the traditional centralized control, decentralized control considers multiple controllers, each with different information structure, actuating a system collaboratively. The thesis is composed of two parts. In the first part, we analyze the system stability of a distribution system with inverter-connected distributed power generation. Inverters are decentralized in nature. They are only allowed to communicate through local system measurements in voltage and current. No direct communication exists between these inverters. This convention of inverter control is nonlinear in the measured voltage and current. This work analyzes how the control policy of droop inverters affects the existing grid, and the robustness of the closed-loop system under disturbances. In the second part, we consider a theoretical problem in decentralized control over an adversarial network. We consider a networked system built on top of unreliable channels. These channels suffer from random information loss. The actuation signal of controllers are carried over a TCP-like protocol. In particular, we consider the sparsity information structure of controllers that are quadratically invariant. The problem is first formulated into a partially observable Markov decision process (POMDP). From the perspective of a fictitious player, we transform this decentralized problem into a centralized problem, which allows us to synthesize an optimal control policy with Kalman filters and value recursions.

Keywords: Electrical Engineering.
Advisor: Gorinevskiĭ D. M. primary advisor.
Lall Sanjay primary advisor. Thesis advisor
Boyd Stephen P. advisor. Thesis advisor
Decision analysis for the optimal treatment of limb threatening leg injuries [electronic resource]

Limb threatening trauma to the leg may be treated with either limb salvage (retention process) or amputation (prosthetic process). Limb salvage allows the patient to keep his leg and avoid using a prosthetic; however, it typically has higher probabilities than amputation of complications, additional time in the hospital, and chronic pain. The optimal treatment is still under debate and the current methods to make the decision do not explicitly incorporate the patient's preferences or the patient's medical insurance. This dissertation develops a decision analysis model to help a patient think clearly about the retention process vs. the prosthetic process. The model updates conditional probabilities of various outcomes based on the patient's demographics and develops a method to explicitly incorporate the patient's preferences for keeping the leg, avoiding chronic pain, and avoiding time in the hospital. The model also calculates the probabilities of hospital and prosthetic costs for the patient's health insurance and risk attitude. The decision analysis model in this dissertation utilizes preferences from the patient to inform the decision, facilitates effective discussions between the doctor and the patient, and provides a comprehensive recommendation to the patient.

Keywords: Management Science and Engineering.
Advisor: Howard Ronald A. (Ronald Arthur)
Bishop Julius advisor. Thesis advisor
Shachter Ross D. advisor. Thesis advisor
Defining and detecting meniscal heterogeneity [electronic resource] : implications on treatment and diagnosis of osteoarthritis

Meniscal degeneration often precedes cartilage degeneration, and effective detection and treatment can be critical in preventing osteoarthritis. The meniscus is a heterogeneous tissue, and obtaining information on the varying characteristics of meniscal regions is important in investigating such strategies. However, no current method exists that can detect such meniscal heterogeneity in the tissue matrix. In addition, the lack of quantitative information on meniscal heterogeneity hinders the development an effective, long-term solution that can treat degeneration in the meniscus. The purpose of this dissertation was thus 1) to find quantitative characteristics that defined meniscal heterogeneity and 2) to evaluate non-invasive diagnostic methods that could reflect the matrix tissue properties and detect meniscal heterogeneity. To accomplish the first goal, gene expression profiles of meniscal cells were statistically analyzed to identify quantitative markers that could distinguish between different regions of the meniscus, describing its heterogeneous properties. This information was then used to evaluate cell sources for meniscal tissue engineering, demonstrating the potential application of these quantitative markers in developing an effective treatment for meniscal degeneration. Secondly, in order to detect meniscal heterogeneity, which is reflected in the changing tissue properties within the tissue, magnetic resonance imaging was used. The potential of the imaging parameters T1[rho] and T2 relaxation times in detecting various meniscal tissue properties, including the matrix composition and mechanical properties, was examined. Ultimately, such information would be useful in identifying internal degenerative changes that take place in the matrix of the tissue prior to macroscopic injuries. In this study, both T1[rho] and T2 relaxation times showed variation with tissue properties but were highly correlated with one another, indicating that only one imaging parameter might be necessary as a diagnostic tool in a clinical setting. In addition, an exploratory aim visualized the internal secondary collagen network in the meniscus and examined its deformation in different mechanical loading positions. This work significantly adds to the understanding of the heterogeneous properties of the meniscus and the potential of magnetic resonance imaging parameters as detection markers. It contributes to the advancement of diagnosis and treatment strategies for meniscal degeneration, which has further implications for preventing osteoarthritis progression.

Keywords: Bioengineering.
Advisor: Levenston Marc Elliot primary advisor. Thesis advisor
Gold Garry E.
Hargreaves Brian Andrew advisor. Thesis advisor
Degenerate ultra-broadband opos for mid-infrared frequency comb generation [electronic resource]

This thesis consolidates an extensive study of optical parametric oscillators (OPOs) optimized for generating extremely broad bandwidth output in the mid-infrared (mid-IR). Optical parametric oscillation is a well-known frequency conversion technique employing an optical element with significant second order nonlinear susceptibility, situated in an appropriate resonator, to convert a shorter wavelength pump laser to longer wavelength OPO outputs. However, our technique is distinct in its optimization for simultaneous oscillation over an extremely broad bandwidth. This is accomplished with a doubly-resonant design, operated at or near degeneracy in a low-dispersion resonator containing a bandwidth-optimized non-linear element and pumped by a mode-locked near-infrared fiber laser. Such an OPO is suitable for generating spectrally and spatially bright, broadband phase- and frequency-locked combs in the absorption-rich mid-IR 'molecular fingerprint' region. Our synchronously pumped system architecture is readily applied to systems operating at other center wavelengths and repetition rates. The comparative simplicity allows new instruments to be envisioned, and is expected to be of great practical interest. Several sync-pumped OPO systems were studied, the first of which are based on periodically poled lithium niobate (PPLN) and pumped by commercial ultrafast erbium fiber lasers at 1.55 µm. With an Er/PPLN OPO system we obtained a pump threshold of 9 mW, output power of 60 mW, and 20dB bandwidth extending from 2.5 to 3.8 µm. Through collaboration, we benefitted from custom orientation patterned gallium arsenide (OP-GaAs) and state-of-the-art femtosecond thulium fiber lasers at 2.0 µm. These components allow us to operate sync-pumped OPOs producing more than 35-mW of output power, 30dB bandwidths extending from 2.6 to 6.1 µm, and pump thresholds of less than 20mW. The broad mid-infrared spectral bands addressed by these sources, combined with the underlying comb structure, make them uniquely suitable for advanced spectroscopic techniques, including "dual-comb" FTIR spectrometry. We have demonstrated the utility and versatility of these OPO sources for sensitive intracavity spectroscopy, remote, and micro-scale spectral absorption measurements.

Keywords: Electrical Engineering.
Advisor: Byer R. L. (Robert L.)
Kasevich Mark A. advisor. Thesis advisor
Nishimura Dwight George advisor. Thesis advisor
Solgaard Olav advisor. Thesis advisor
Vodopyanov Konstantin L.
Degradation of cartilage and meniscus tissues [electronic resource] : an in vitro investigation in osteoarthritis development

Osteoarthritis is a debilitating disease that affects 27 million Americans. Major risk factors for osteoarthritis include mechanical injury and obesity. Prolonged exposure to mechanical overload in the knee joint, either by injury, malalignment, or obesity, is associated with early onset of osteoarthritis. Recent evidence demonstrates that adipose tissue is a metabolically active and produces systemic biofactors known as adipokines associated with numerous diseases including cardiovascular disease, hypertension, insulin resistance, rheumatoid arthritis, and osteoarthritis. Interestingly, obesity is a significant risk factor for hand osteoarthritis, suggesting a biologic link between obesity and osteoarthritis that is perhaps mediated through adipokines. While many studies investigating in vitro osteoarthritic degradation have focused on cartilage tissue, the menisci has received relatively little attention despite it's important functional role in joint stability and load transfer in the knee. The purpose of this thesis was to explore the relative susceptibility of cartilage and meniscal tissue degradation to in vitro mechanical overload and adipokine exposure using an immature bovine tissue explant model. To explore the injury response, explants of cartilage and meniscal tissues were compressed at various strain rates to create a spectrum of peak injury forces and cultured for up to nine days post-injury. To investigate whether adipose tissue and adipokines can biochemically induce changes in cartilage and meniscal tissues, explants of cartilage and meniscal tissue were incubated with infrapatellar fat pad or individual adipokines and assessed for altered matrix metabolism. Overall, results indicate that, while mechanically robust, meniscal tissue is vulnerable to biologic damage induced by mechanical overload and adipokines. We also demonstrate for the first time that meniscal tissue is more catabolically sensitive to adipokines than cartilage tissue. These results provide evidence that obesity-driven degradation of knee joint could be biochemically mediated and suggest meniscal degradation as a possible early event in osteoarthritis development.

Keywords: Mechanical Engineering.
Advisor: Levenston Marc Elliot primary advisor. Thesis advisor
Andriacchi Th. P. (Thomas P.) advisor. Thesis advisor
Goodman Stuart advisor. Thesis advisor
Smith R. Lane (Robert Lane) advisor. Thesis advisor
Derivative-free optimization for generalized oil field development [electronic resource]

Given the substantial costs and potential rewards associated with petroleum field development and reservoir management, it is essential that these operations be performed as close to optimally as possible. This work presents numerical methods for field development optimization where the goal is to simultaneously determine the optimal number and type of new wells, the sequence in which they should be drilled, as well as their corresponding locations and (time-varying) controls. The optimization is posed as a mixed-integer nonlinear programming (MINLP) problem and involves categorical, integer-valued, and real-valued variables. The formulation handles bound, linear, and nonlinear constraints; the latter are treated using filter-based techniques. Noninvasive derivative-free approaches are applied for the optimizations. Methods considered include Mesh Adaptive Direct Search (MADS, a local pattern search method), Particle Swarm Optimization (PSO, a heuristic global search method) and a PSO-MADS hybrid. Single and biobjective optimization example cases are presented. These cases involve well control optimization, joint well placement and control, and generalized full-field development problems. Significant improvement over base-case field development plans is demonstrated in all cases and the PSO-MADS hybrid procedure is shown to outperform its component methods. It is concluded that, although demanding in terms of computation, the methodology presented here is applicable for realistic petroleum field development and reservoir management.

Keywords: Energy Resources Engineering.
Advisor: Durlofsky Louis primary advisor. Thesis advisor
Aziz Khalid advisor. Thesis advisor
Mukerji Tapan
Design and development of a 1mm resolution clinical positron emission tomography (PET) system [electronic resource]

Positron Emission Tomography (PET) is an in-vivo medical imaging modality that extracts information about molecular processes associated with disease. A PET system produces an image of radiopharmaceuticals that have preferentially accumulated in certain cells of tissues in the body, such as cancerous lesions. Clinical PET systems have about 5-10mm spatial resolution, and thus have difficulty resolving very small lesions. So, improving the resolution of PET is an active area of research. This thesis describes the design of a 1mm resolution PET system for breast cancer imaging and the strategies used to overcome the challenges of developing such a high resolution PET system. The detectors in this PET system consist of lutetium yttrium oxyorthosilicate (LYSO) scintillation crystal arrays coupled to position-sensitive avalanche photodiodes (PSAPDs). There will be over 2000 Dual-LYSO-PSAPD detector modules in the final system, each requiring a bias voltage of 1750 Volts. A programmable high voltage distribution method allows the bias voltage to be optimized for each detector module. Multiplexing of detector signals reduced the number of interconnects by 40% and front-end electronic channels by 33%. Charge division and charge sharing signal conditioning compensate for the mismatch between the detector signal and the front-end electronics input dynamic range, as well as for parasitic capacitance introduced by interconnect. A model of the detectors and electronics was created to help understand the system and to assist in the system design process. Two cartridges of the system, consisting of 256 Dual-LYSO-PSAPD detectors, were constructed and characterized. The system energy resolution was 11% FWHM (full-width-at-half-maximum) and the measured spatial resolution was less than 1mm. The system was able to produce reconstructed images of a phantom with 1.2mm rods filled with a solution of the positron emitter Fluorine-18.

Keywords: Electrical Engineering.
Advisor: Levin Craig primary advisor. Thesis advisor
Horowitz Mark (Mark Alan) advisor. Thesis advisor
Wooley Bruce A.
Design mining the web [electronic resource]

The billions of pages on the Web today provide an opportunity to understand design practice on a massive scale. Each page comprises a concrete example of visual problem solving, creativity, and aesthetics. In recent years, data mining and knowledge discovery have revolutionized the Web, driving search engines, advertising platforms, and recommender systems that are used by more than two billion people every day. However, traditional data mining techniques tend to focus on the content of Web pages, ignoring how that content is presented. What could we learn from mining design? This thesis introduces design mining for the Web, and presents a scalable software platform for Web design mining called Webzeitgeist. Webzeitgeist consists of a repository of pages processed into data structures that facilitate large-scale design knowledge extraction. With Webzeitgeist, users can find, understand, and leverage visual design data in Web applications. In this dissertation, I demonstrate how software tools built on top of Webzeitgeist can be used to dynamically curate design galleries, search for design alternatives, retarget content between page designs, and even predict the semantic role of page elements from design data. As more and more creative work is done digitally and shared in the cloud, Webzeitgeist illustrates how design mining principles can be applied to benefit content creators and consumers.

Advisor: Klemmer Scott primary advisor. Thesis advisor
Hanrahan P. M. (Patrick Matthew) advisor. Thesis advisor
Winograd Terry advisor. Thesis advisor
The design of an efficient vector virtual machine for data analytics [electronic resource]

The amount of parallelism available in commodity hardware has been steadily increasing. Recent hardware trends suggest that within the next few years, widely available computers will boast substantial parallelism--8 or more cores, each supporting hardware vectorized operations on 4 or more double-precision floating point values at a time. In parallel with this development, the rise of big data, and data science more generally, has created enormous interest in analytics that can extract value from data. However, the most popular languages for data analysis and statistical computing--R, Matlab, Python, and Excel--are designed for ease of use, not performance, and their current implementations may see little performance gains from the increasing parallelism of commodity hardware. This dissertation focuses on the design of virtual machines that aim to deliver the full performance potential of upcoming commodity-level parallel hardware while still providing a high-level, easy-to-use analytic experience. First, this dissertation describes Riposte, a JIT compiler for the R language, designed to execute vector code on parallel hardware. To execute code with scalars and short vectors, Riposte uses a tracing-based approach adapted from recent Javascript VM work to extract hot loops. It then uses a novel partial length specialization pass to eliminate loop overhead and promote vectors into hardware SIMD units. To execute long vector code, Riposte uses a delayed evaluation approach to dynamically discover and extract sequences of vector operations. Once extracted, it then fuses operations to eliminate unnecessary memory traffic and then schedules them to run across multiple cores. On a variety of analytic workloads, we demonstrate that Riposte can run R code at near the speed of optimized C and for data parallel workloads we demonstrate good scalability out to 32 cores. At a high level, Riposte demonstrates that a vector-based, dynamically typed language can be an effective and efficient parallel programming model for data analysis tasks. Second, this dissertation describes Phoenix++, a C++ library for MapReduce-style computation on shared memory machines that leverages compile-time specialization to generate high quality parallel code while greatly reducing the amount of code that users must write. We validate the approach by implementing a variety of common analytic workloads in Phoenix++ and demonstrating substantial speed up and improved scalability compared to previous work.

Advisor: Hanrahan P. M. (Patrick Matthew) primary advisor. Thesis advisor
Heer Jeffrey Michael advisor. Thesis advisor
Kozyrakis Christoforos