VictorJuiz/thesis huggingface dataset:
Atomically Thin Processing of High Surface Area Nanomaterials for Electrochemical Energy Devices

As interest in renewable energy grows on both research and policy fronts, energy storage likely represents one of the most viable solutions to the problems posed by the intermittency and irregularity of renewable resources. While new classes of materials promise improved performance of energy storage systems, understanding energy storage electrode architecture and fabrication at the micro-scale allows us to fully leverage performance along different dimensions./nThis dissertation aims to explore the use of device architecture manipulation to improve energy storage and conversion electrodes, focusing on addressing challenges around manufacturing high-surface area electrodes. Phsyically, our approach to texturizing electrodes consists of synthesizing materials as to create high-surface area templates while physically manipulating the electrode to maximize performance. Chemically, we manipulate performance with Angstrom-level precision, utilizing atomically thin layers to induce chemical enhancement of our devices at the electrode interface./nThe principles of leveraging physical and chemical manipulation of electrodes is demonstrated in five unique works: (1) atomic layer deposition of titanium-nitride on carbon nanotubes for supercapacitor applications, (2) two-dimensional iron-phosphate for supercapacitor applications, (3) thiophene-based electrodeposition for photoelectrochemical water splitting, (4) titanium dioxide-coated zinc oxide nanowire arrays for photoelectrochemical water splitting, and (5) development of atomic layer deposited black titania for photoelectrochemical water splitting.

Advisor: Lin, Liwei
Combining Speech and Speaker Recognition - A Joint Modeling Approach

Automatic speech recognition (ASR) and speaker recognition (SRE) are two important fields of research in speech technology. Over the years, many efforts have been made on improving recognition accuracies on both tasks, and many different technologies have been developed. Given the close relationship between these two tasks, researchers have proposed different ways to introduce techniques developed for these tasks to each other./nIn the first half of this thesis, I explore ways to improve speaker recognition performance using state-of-the-art speech recognition acoustic models, and then research alternative ways to perform speaker adaptation of deep learning models for ASR using speaker identity vector (i-vector). Experiments from this work shows that ASR and SRE are beneficial to each other and can be used to improve their performance./nIn the second part of the thesis, I aim to build joint model for speech and speaker recognition. To implement this idea, I first build an open-source experimental framework, TIK, that connects well-known deep learning toolkit Tensorflow and speech recognition toolkit Kaldi. After reproducing state-of-the-art speech and speaker recognition performance using TIK, I then developed a unified model, JointDNN, that is trained jointly for speech and speaker recognition. Experimental results show that the joint model can effectively perform ASR and SRE tasks. In particular, experiments show that the JointDNN model is more effective in speaker recognition than x-vector system, given a limited amount of training data.

Advisor: Morgan, Nelson
Fast and Stable Low-Rank Symmetric Eigen-Update

Updating the eigensystem of modified symmetric matrices is an important task arising from certain fields of applications. The core of the problem is computing the eigenvalues and orthogonal eigenvectors of a diagonal matrix with symmetric low rank modifications, {\em i.e.} $D + UHU^T$. The eigenproblem of this type of matrix has long been studied since Golub et.al~\cite{pa} proposed theoretical considerations about it. Currently, there exist methods to compute eigenvalues accurately, but the difficulty remains in numerical stability and orthogonality of computed eigenvectors./nThe main contribution of this thesis is a new method to compute all the eigenvalues and eigenvectors of a real diagonal matrix with a symmetric low rank perturbation. The algorithm computes an orthogonal matrix $Q = [q_1, q_2, \ldots, q_n]$ and a diagonal matrix $\Lambda = diag\{\lambda_1, \lambda_2, \ldots, \lambda_n\}$ such that $AQ = Q\Lambda$. Here the matrix $A = D + UHU^T$ has the special structure that $D \in\mathbb{R}^{n\times n}$ is a diagonal matrix, $U\in\mathbb{R}^{n\times r}$ is a column orthorgonal matrix and $H\in\mathbb{R}^{r\times r}$ is a symmetric matrix. $n$ is the dimension of $A$ and $r</nAside from solving the eigensystem update problem mentioned above, our proposed method can also be used in the divide and conquer eigenvalue algorithm. Cuppen's divide and conquer algorithm~\cite{cuppen} solves a rank-one update of eigensystem in its merge step for a symmetric tri-diagonal matrix. A symmetric banded matrix will require solving the eigensystem of a low-rank perturbed diagonal matrix, {\em i.e.}, $D+UHU^T$. Efficient solution to this problem in the merge step can potentially enable application of divide and conquer algorithm directly on symmetric banded matrix./nIn our proposed algorithm, eigenpairs are mostly computed by Rayleigh Quotient Iteration safe-guarded with bisection, with each eigenpair requiring $O(nr^2)$ flops to compute. Hence the overall computational complexity for our algorithm is $O(n^2r^2)$. This is an appealing quadratic algorithm since $r$ is usually considered a small constant relative to $n$. To ensure numerical stability, eigenvectors corresponding to eigenvalue clusters are computed through a special \textit{orthogonal deflation} method that completely avoids re-orthogonalization. In case of tight clusters, extended precision arithmetic is used for eigenvectors corresponding to close eigenvalues./nWe present both theoretical analysis and numerical results to support our claim that the proposed algorithm is numerically stable.

Advisor: Gu, Ming
Educational Recontextualization in Uganda: Seeking Flexibility and Variation in an Era of Transnational Isomorphisms

Within the field of comparative and international education (CIE), two important narratives have emerged in analyzing global and local influences on international education. One, advanced by world culture theorists, argues that Western supranational influences on national education systems has led to homogeneity—or isomorphism—in educational structures, policies, and practices around the world. The other, advanced by many in the educational policy borrowing and lending field, prioritizes local efforts to indigenize, or recontextualize, educational policies and practices rather than focus on external influences. In this study, consideration is given to both the global and the local narrative on education in Uganda./nThis is achieved over two sections. Part I closely analyzes of the evolution of educational policy in Uganda, tracing prominent transnational isomorphisms—most notably the hegemony of colonial education—across multiple eras. In Part II, two case studies of educational NGOs in Uganda explore alternative approaches to the recontextualization of transferred educational ideas and programs. The case examining Educate! and its Educate! Experience program offers a glimpse into negotiated recontextualization, while the case examining the Kimanya-Ngeyo Foundation and its imported Preparation for Social Action program offers a picture of decentralized recontextualization. In the end, recommendations are made to the field of CIE regarding the responsible transfer and recontextualization of educational program and practices within an era of transnational isomorphisms.

Advisor: Murphy-Graham, Erin
Mahiri, Jabari
Domain-Specific Techniques for High-Performance Computational Image Reconstruction

The widespread emergence of parallel computers in the last decade has created a substantial programming challenge for application developers who wish to attain peak performance for their applications. Parallel programming requires significant expertise, and programming tools---general-purpose languages, compilers, libraries, etc.---have had limited success in hiding the complexity of parallel architectures. Furthermore, the parallel programming burden is likely to increase as processor core counts grow and memory hierarchies become deeper and more complex./nThe challenge of delivering productive high-performance computing is especially relevant to computational imaging. One technique in particular, iterative image reconstruction, has emerged as a prominent technique in medical and scientific imaging because it offers enticing application benefits. However, it often demands high-performance implementations that can meet tight application deadlines, and the ongoing development of the iterative reconstruction techniques discourages ad-hoc performance optimization efforts./nThis work explores productive techniques for implementing fast image reconstruction codes. We present a domain-specific programming language that is expressive enough to represent a variety of important reconstruction problems, but restrictive enough that its programs can be analyzed and transformed to attain good performance on modern multi-core, many-core and GPU platforms. We present case studies from magnetic resonance imaging (MRI), ptychography, magnetic particle imaging, and microscopy that achieve up to 90% of peak performance. We extend our work to the distributed-memory setting for an MRI reconstruction task. There, our approach gets perfect strong scaling for reasonable machine sizes, and sets the best-known reconstruction time for our particular reconstruction task. The results indicate that a domain-specific language can be successful in hiding much of the complexity of implementing fast reconstruction codes.

Advisor: Yelick, Katherine
Fox, Armando
“To seek new friends and stranger companies”: The Expansion of Friendship in Early Modern England

This dissertation argues that an acknowledgment of disparity was central to the conception of early modern friendship and that the period’s emphasis on such disparity authorized the creation of larger social groups and networks. Classical theory’s emphasis on likeness and parity in friendship offered a crucial model and rhetoric for conceiving ideal social relations. Renaissance writers, however, highlighted the inescapability of difference in an emerging set of social, political, and economic possibilities. Rather than read this difference as a loss of friendly idealism, they articulated the ways in which such difference might sustain existing likeness-based bonds as well as engender a larger number of social relations. A disparity between friends, Shakespeare and his contemporaries believed, would generate an expansive cultivation—rather than a mere reflection—of virtue; the promise of such virtuous expansion in turn encouraged friends to seek a greater number and range of social connections. The celebration of such pluralist configurations in Renaissance literature challenges the conception of social life as a search for exclusive union with a single individual and allows us to recognize the ways in which disparate qualities and experiences actually facilitated the creation of social connections over the course of the early modern period.

Advisor: Knapp, Jeffrey
Discrete Elastic Rods for Simulating Soft Robot Limbs

Discrete elastic rods (DER) is a recent formulation of a rod theory by Bergou et al. The material curve of the rod is approximated by a discrete set of lines connected at vertices. The formulation originated in the field of computer graphics and uses concepts from the nascent field of discrete differential geometry to characterize bending energies and torsional strains. Specifically, the discrete curvature vector associated with a vertex is used as a measure of bending strain and the length of the edges are used to account for stretching. Additionally, each edge is associated with a reference frame and a material frame, where the angle difference of the latter frame between adjacent edges is a measure of twist. Space- and time- parallel transport operators are introduced to update these frames in space and time respectively, so the torsion of the rod can be efficiently computed./nWhile DER is an elegant formulation, it is challenging to comprehend. In this dissertation, complete derivations for the expressions for the variations, gradients, and Hessians of kinematic variables induced by changes to the vertices are presented. These gradients are needed to numerically solve the governing equations of motion. The method by which a component of the rotation of the cross section is computed in the discrete elastic rod formulation is exceptional and exploits a phenomenon in differential geometry known as a holonomy. Relevant background from differential geometry and spherical geometry are presented to understand how the reference twist in the rod can be related to a solid angle enclosed by the trace of a unit tangent vector on a sphere and several examples are presented to illuminate the calculation of twist./nThe second part of the dissertation is devoted to using the DER formulation to examine the dynamics of soft robots. To this end, a planar formulation of DER (PDER) is derived. Our work allows the governing equations of a discrete rod to be expressed in a canonical using Lagrange’s equations. This in turn allows us to use PDER with folded and branched elastic structures which feature in the designs of soft robots. To illustrate our developments, PDER is used to formulate and analyze the equations of motion needed to simulate the locomotion of a caterpillar-inspired soft robot on a rough surface.

Advisor: O'Reilly, Oliver
Study of Dynamics and Nanoscale Heat Transfer of Head Disk Interface in Hard Disk Drives

Since its introduction in 1956, hard disk drives have become one of the dominant products in the industry of data storage. The capacity of the hard disk drives must keep evolving to store the exploding data generated in the era of big data. This demand pushes the development of technologies including heat assisted magnetic recording (HAMR), microwave assisted magnetic recording (MAMR) and bit-patterned media (BPM) to increase the areal density beyond 1Tb/in2. In the development of these technologies, it is essential to have a clear understanding of the dynamics and nanoscale heat transfer behavior across the head-disk interface./nIn this dissertation, dynamics and nano-scale heat transfer in the head disk interface are discussed. Experimental study of nano-scale heat transfer is conducted with the specifically designed static touchdown experiment. Simulation strategy that incorporates the wave-based phonon conduction theory was also developed./nIn the flying condition, correlation between the temperature and head disk spacing was found at both passive flying stage and modulation stage. When the flying height increases due to either disk surface microwaviness or contact induced modulation, head temperature will increase, with a slight time delay, indicating the existence of a cooling effect as the head approaches the disk./nThe static touchdown experiment, which decouples the complicated air bearing from the nano-scale interface was further designed and performed. The heat transfer behavior across a closing nano-scale gap between head and disk was observed and measured. Experimental and simulation results showed general agreement with the theoretical predictions of the wave based theory for radiation and phonon conduction. The effect of different factors including humidity, air pressure, lubricant layer and disk substrate in the static touchdown experiment were also studied separately./nFurthermore, the dynamics of HAMR condition was studied with waveguide heads. The laser induced protrusion was found to be around 1~2 nm in height./nThe findings of this dissertation could be applied to future HAMR head/media design, and the static touchdown experiment could be potentially improved to be a new approach to measure material conduction coefficient and emissivity with high special resolution.

Advisor: Bogy, David B
Using X-ray Thomson Scattering to Measure Plasma Conditions in Warm Dense Matter Experiments on the OMEGA Laser

High energy density physics (HEDP) is an emerging field that seeks to investigate the properties of matter at extreme conditions. High energy density conditions occur in materials with pressures exceeding 1 Mbar, or pressures that exceed Earth’s atmospheric pressure by a factor of more than a million. A regime of HEDP of particular interest is warm dense matter (WDM) physics, which describes the behavior of materials at near solid densities and 10’s of eV temperatures. WDM occurs in astrophysical objects, such as giant planets and brown dwarfs, and is also generated in inertial confinement fusion (ICF) experiments. X-ray Thomson scattering (XRTS) offers a powerful tool to probe the equation of state of WDM. XRTS spectra consist of two components: elastically scattered photons with the frequency of the original x-ray source and inelastically scattered photons that are down- shifted in frequency. The Compton-shifted profile of inelastically scattered x-rays can be analyzed to return the sample’s electron density and electron temperature. The ratio of elastically to inelastically scattered x-rays relates to the number of tightly bound versus free electrons, and thus reflects the ionization state./nThis thesis discusses the results of XRTS experiments on WDM performed at the OMEGA Laser facility. The first experiment presents and discusses XRTS results from 1 mm diamond spheres. The scattering spectra show evidence of higher ionization than predicted by several commonly-applied ionization models. A second experiment analyzed the contributions to elastic scattering from a small argon impurity in imploding beryllium capsules. The exper- iment found that less than 1 at.% of argon significantly affects the elastic scattering signal strength, and concluded that impurities in a sample should be considered before drawing conclusions from elastic scattering signals. The final experiment uses XRTS to measure the electron temperature and ionization state in isochorically heated materials used in ion stopping power experiments. The results from these experiments demonstrate the power of XRTS to measure ionization in WDM to benchmark theoretical modeling.

Advisor: Falcone, Roger W
Doeppner, Tilo
Continuous Commissioning of Buildings: HVAC Fault Detection and Diagnosis

It is almost certain that all systems contain faults, and Heating, Ventilation, and Air Conditioning (HVAC) systems are no exception. About 41% of total energy consumption in the U.S. of year 2014 is used for heating and air conditioning, that is about 40 quadrillion (10^15) British thermal units (BTU)! In the past, fault detection and diagnosis (FDD) has been commissioned by man, which is costly and inefficient. If FDD can be done automatically and continuously, a great amount of energy could be saved and our buildings would become more sustainable./nPeople have been working on HVAC FDD for years, and will continue to make progress. However, buildings are complicated, and so are the HVAC systems which comes with them. Thanks to the fast growth of computers and developments of machine learning algorithms in recent years, we have more tools to work with./nIn despite of many researches done on HVAC FDD, we have noticed that very few publications have focused on scalability and low cost. In order to address this challenge, we will propose an approach which focuses on control data. In this thesis, we will be relying on simulation data because of data access issues and the lower cost for experiments. A list of machine learning algorithms are introduced for data exploration and analysis, a control data focused model free approach is presented as well, and finally, FDD is carried out by implementing anomaly algorithms.

Advisor: Auslander, David M
Essays on the Economics of Urban Crime

This dissertation focuses on what determines crime and victimization in the urban space. The theoretical basis of this work strongly rests on the contributions of Gary Becker and Ronald V. Clarke to the crime literature. Chapter one offers a brief and selected overview of many important contributions in the economics of crime literature. I focus on some particular puzzles and the kind of solutions that have been offered in the last fifty years where the understanding regarding the role of prisons as a crime-control policy tool is critically assessed. I emphasize the complexity and multi-causal nature of crime as a way to motivate the theoretical and empirical contributions of chapters two and three. In the following chapters I pay special attention on how criminal activity reacts to changes in incentives or situational factors under different theoretical and empirical settings. Chapter two is devoted to understand criminal activity in the public transportation sector which represents a salient place where criminal activity takes place. I incorporate a simple model of offenders and victim's interactions to describe how victim's behavior reacts and determines the set of criminal opportunities available for potential offenders. Empirically, I exploit a set of subsequent reforms in the public transportation system where variations to driver's incentives as well as the availability of cash substantially altered the amount and the nature of criminal activity observed. In chapter three, jointly written with Kenzo Asahi, we study the effect of a particular situational factor such as ambient light on crime. In both cases, the evidence I find supports the relevance of incentives. I identify specific policy changes or situational deviations whose effects in terms of criminal victimization can be equivalent to enormous public policy interventions in terms of prosecution. All findings presented in this dissertation attempts to enlarge the growing body of scientific understanding regarding criminal activity in urban areas.

Advisor: Raphael, Steven