VictorJuiz/thesis huggingface dataset:
Deep neural networks in speech recognition [electronic resource]

Spoken language is an increasingly pervasive interface choice as computing devices permeate many aspects of daily life. Automatically understanding spoken language poses significant challenges because it requires both converting a speech signal into words and extracting meaning from the words themselves. Spoken language understanding tasks can roughly be broken into distinct components which perform (1) low-level processing of the audio signal, (2) speech transcription, and (3) natural language understanding. We describe approaches to improving individual components for each sub-task associated with spoken language understanding. Our methods primarily rely on machine-learning-based approaches to replace hand-engineered approaches and consistently find that learning from data with minimal assumptions about a problem results in improved performance. In particular, we focus on neural network approaches to problems. Neural networks have seen a recent resurgence of interest thanks to their ability to scale to learn increasingly complex functions when more data becomes available. Neural networks have recently driven tremendous progress in the field of computer vision, where many tasks easily translate into classification and regression problems. In spoken language understanding, however, it is more difficult to define tasks which are easily formalized into problems for a neural network to solve. Our work integrates with these complex systems and shows that, like in computer vision, neural networks can significantly improve spoken language understanding systems.

Advisor: Ng Andrew Y.
Jurafsky Dan
Liang Percy advisor. Thesis advisor
Default prediction for small businesses [electronic resource]

Small business loan defaults have been an active research area. Two major families of default prediction models are reduced form models and structural form models. Reduced form models focus on finding the statistical relations between default events and various economic variables, while structural form models focus on describing default event as a stopping time of some stochastic process. First we propose a reduced form model that uses massive amounts of data mined from the internet to supplement traditional economic variables in the data set. We compared the performance of reduced form models using internet covariates versus those using traditional covariates, and explored the possibility of a hybrid model using both types of covariates. Secondly, we propose a structural form model where we integrate the impact of relationship lending, a practice that has achieved success in recent years, into an incomplete information model. Numerical results are provided for both models.

Keywords: Management Science and Engineering.
Advisor: Giesecke Kay primary advisor. Thesis advisor
Infanger Gerd
Lai T. L. advisor. Thesis advisor
Defining the Interactions Between Chromatin Remodeler INO80 and Microtubules

Chromatin remodelers are protein complexes characterized by their role in manipulating and modifying chromatin and histones. They are known to regulate transcription and DNA damage response, but recent discoveries suggest they also regulate chromosome segregation and other aspects of mitosis, proposing a novel and undefined role for chromatin remodelers. Such is the case for INO80, a well studied 15 subunit protein complex. Preliminary data show a likely interaction between INO80 and microtubules, both of which are essential for proper chromosome segregation and correctly positioning components of the dividing cell. Thus, to maintain proper chromosome segregation and cell division, we hypothesize that the INO80 complex plays a vital role in mitosis by binding to and stabilizing microtubules. Using yeast genetics in S. cerevisiae, we found a strong association between the INO80 complex and tubulin after immunoprecipitation and separation by molecular density on a sucrose gradient. We next investigated this interaction in mutants of the various INO80 modules further to characterize each mutant’s relationship with microtubules. It was found that the N-terminal region of Ino80 was necessary for its association with tubulin. Furthermore, we investigated the DNA content of each mutant using FACS as well as its response to microtubule destabilizing agents in a fitness assay. Overall, investigating the role of chromatin remodeler INO80 in mitosis may elucidate a mechanism for developing chromosomal and other mitotic defects dependent on interactions between INO80’s subunits and microtubules. This mechanism of action may help characterize and explain the presence of mitotic defects in cancer cells.

Keywords:  Department of Biology
biology
Stanford University
cancer biology
molecular biology
chromatin remodeler
INO80
mitosis
microtubule
tubulin
Saccharomyces cerevisiae
Thesis
Advisor: Morrison Ashby
Stearns Tim
Demographic and selective inference in great apes [electronic resource]

Humans and other great apes have intricate evolutionary histories, shaped by numerous demographic and selective events. A wealth of new genomic data provides the foundation for key insights into some of this complexity. This thesis develops tools for population genetic analyses, provides genome-wide insights into gorilla population genetics, and delivers fine-scale understanding of a specific human disease resistance allele. The chapters of this thesis provide complementary genome-wide and localized insights into great ape evolutionary history. Chapter 2 details a genetic simulation software that generates large-scale genetic data in flexible scenarios. Chapter 3 describes a study on the demographic and selective history of gorillas; we find a significant population contraction during the last glacial maximum (20 kya) in western lowland gorillas and evidence of positive selection in genes related to heart function and bitter taste perception. Chapter 4 is an in-depth analysis of one of the most population differentiated loci in the human genome, the DARC gene, which is known to provide resistance to a malaria-causing protozoan. We explore this gene's population genetics, including its geographical distribution and signatures of natural selection, as well as infer the mode and magnitude of selection on the malaria resistance allele. These chapters emphasize the importance of population genetics at various scales. Genome-wide methods allow identification of global trends, while in-depth analyses of specific loci provide insights into specific events and selective pressures shaping our genomes, and complement our large-scale inferences. This dissertation develops generalizable methods, achieves novel biological insights, and broadens our understanding of great ape evolutionary history.

Keywords: Biology.
Advisor: Bustamante Carlos (Carlos D.) primary advisor. Thesis advisor
Montgomery Stephen
Petrov Dmitri Alex
Pritchard Jonathan (Jonathan K.) advisor. Thesis advisor
Design and analysis of numerical methods for free- and moving-boundary problems [electronic resource]

This thesis presents the design and analysis of numerical methods for free- and moving-boundary problems: partial differential equations posed on domains that change with time. Two principal developments are presented. First, a novel framework is introduced for solving free- and moving-boundary problems with a high order of accuracy. This framework has the distinct advantage that it can handle large domain deformations easily (a common difficulty faced by conventional deforming-mesh methods) while representing the geometry of the moving domain exactly (an infeasible task for conventional fixed-mesh methods). This is accomplished using a universal mesh: a background mesh that contains the moving domain and conforms to its geometry at all times by perturbing a small number of nodes in a neighborhood of the moving boundary. The resulting framework admits, in a general fashion, the construction of methods that are of arbitrarily high order of accuracy in space and time when the boundary evolution is prescribed. Numerical examples involving phase-change problems, fluid flow around moving obstacles, and free-surface flows are presented to illustrate the technique. Second, a unified analytical framework is developed for establishing the convergence properties of a wide class of numerical methods for moving-boundary problems. This class includes, as special cases, the technique described above as well as conventional deforming-mesh methods (commonly known as arbitrary Lagrangian-Eulerian, or ALE, schemes). An instrumental tool developed in this analysis is an abstract estimate, which applies to rather general mesh motions, for the error incurred by finite element discretizations of parabolic moving-boundary problems. Specializing the abstract estimate to particular choices of the mesh motion strategy and finite element space leads to error estimates in terms of the mesh spacing for various semidiscrete schemes. We illustrate this by deriving error estimates for ALE schemes under mild assumptions on the nature of the mesh deformation and the regularity of the exact solution and the moving domain, and we do the same for universal meshes.

Advisor: Lew Adrian primary advisor. Thesis advisor
Farhat Charbel advisor. Thesis advisor
Papanicolaou George advisor. Thesis advisor
Design and development of data acquisition electronics for a 1 mm resolution clinical Positron Emission Tomography (PET) system [electronic resource]

Positron Emission Tomography (PET) is a functional medical imaging modality often used for cancer imaging. A typical clinical PET scanner will have a resolution greater than 5 mm. This resolution cannot resolve small cancerous lesions and may cause some lesions to be missed. This dissertation describes the design of a 1 mm3 resolution breast-dedicated clinical PET scanner which will provide the ability to identify smaller lesions and improve breast cancer screening or treatment. The PET scanner achieves this resolution by decreasing the dimensions of the PET scintillation detection elements to 1x1x1 mm3, creating a 3D position sensitive scintillation detector system, and placing the panels up against the breast. The scanner design uses 4608 basic detector units, each of which comprise position sensitive avalanche photodiodes (PSAPDs) coupled to 8x8 arrays of 1x1x1 mm3 LYSO scintillation crystal elements, requiring 18,432 readout channels. This dissertation details and evaluates the electronic architecture required to synchronize and readout the signals from the densely packed detectors. It also describes the signal processing performed on the signals to maximize the capability of the system.

Keywords: Electrical Engineering.
Advisor: Levin Craig primary advisor. Thesis advisor
Fox John D. advisor. Thesis advisor
Pauly John (John M.) advisor. Thesis advisor
Design and fabrication of nanofluidic transistors beyond Debye screening limit [electronic resource]

The development of microfluidic systems, which miniaturize complex laboratory pro- cedures onto small microchips, has dramatically reduced the cost and time of biologi- cal analyses. With fluidic devices scaling down to nanometer regime, new phenomena that were previously inaccessible at larger length scales arise. Particularly, electro- static force can now be used to control ionic and biomolecule transport in nanofluidic devices. Nanofluidic devices using an active gate to manipulate charged molecules called nanofluidic transistors by analogy to MOSFET transistors, have applications ranging from sample preparation in point-of-care devices to sample sorting, and sea- water desalination. In ionic solutions, the Debye Length is considered as the characteristic length scale for effective field-effect control. Hence, the state-of-the-art nanofluidic transis- tors presented in the literature have required at least one dimension comparable to or smaller than Debye Length (sub-10 nm--30 nm) to achieve sufficient electrostatic control. This limit imposes challenges and difficulties on device fabrication. Simu- lations based on coupled Poisson-Nernst-Plank-Stokes models show that strong ionic transport can overcome the Debye-screening limits, thus leading to field-effect control beyond Debye Length. This thesis therefore focuses on the design and fabrication of nanofluidic transistors with channel size 100 nm to 200 nm, far beyond Debye Length limits (typically 10 nm in 1 mM concentration solutions), while achieving efficient field effect control. Further, a novel dual-gate configuration is introduced to improve nanofluidic transistors' current modulation ratio. Two possible device structural configurations—vertical channel and lateral channel devices—are proposed and compared with regards to their fabrication feasibilities and performances; both fabrication flows are compatible with conventional semicon- ductor fabrication technologies. The measurement results of NFTs beyond Debye- screening limit demonstrate highly effective electrostatic control of ions. In vertical channel devices, current modulation rate is 6-fold by using 1 V bias; in lateral channel devices, 2.6X current modulation rate is achieved by ∼10 V bias. Both results are better than the conventional Debye Length limited nanofluidics transistors. The nanofluidic transistors beyond Debye-screening limit demonstrate a new op- erating regime. The relaxed constraint on channel sizes offers advantages in device manufacturing, testing, and reliability. Based on standard process flows for fabrica- tion, this work also opens up the possibilities of on-chip fluid system integration as well as new applications in biological sensing and sample preparation.

Keywords: Electrical Engineering.
Advisor: Dutton Robert W. primary advisor. Thesis advisor
Howe Roger Thomas advisor. Thesis advisor
Wang Shan
The design and implementation of large-scale graph analysis language [electronic resource]

With the rise of worldwide social networking services, large-scale graph analysis has become important. Because of a lack of high-level programming models, MapReduce or Pregel are used for large-scale graph analysis, but require much effort to implement even simple analyses. For greater ease of use and efficiency, we propose SociaLite, a high-level graph query language based on Datalog. As a logic programming language, Datalog allows many graph algorithms to be expressed succinctly. However, its performance has not been competitive when compared to imperative programming languages. With SociaLite, users can provide simple annotations to the data layout and evaluation order; they can also define recursive aggregate functions, which can be evaluated incrementally and efficiently. Moreover, SociaLite is extended to provide high-level abstractions for distributed computation. These extensions allow users to simply annotate how data is to be distributed; then SociaLite compiler automatically generates parallel code for a cluster of multi-core machines. The evaluation of recursive aggregate functions is optimized with a delta-stepping technique on a distributed cluster. In addition, approximate computation is supported in SociaLite, allowing users to trade off accuracy for less execution time and storage space. We evaluated SociaLite with core graph algorithms, including shortest paths and PageRank, that are commonly used in graph analyses. With its optimizations to Datalog, SociaLite is shown to be much faster than Datalog, and as fast as highly optimized Java. When evaluated on a multi-core machine, SociaLite programs scaled linearly up to 16 cores, except for the shortest paths program which showed a speedup of 10 on 16 cores. In our experiment with 64 Amazon EC2 instances, SociaLite programs tracked the ideal weak scaling curve within a factor of two. Compared to Giraph, an open-source version of Pregel, SociaLite programs are 4 to 12 times faster across benchmark algorithms and 22 times more succinct on average. We also extensively evaluated state-of-the-art graph systems, GraphLab, Combinatorial BLAS, as well as Giraph, and compared their programmability and performance with SociaLite. From the evaluation, we found that SociaLite provides the simplest programming model; for BFS (Breadth First Search) algorithm, the SociaLite program is 10 times more succinct than the equivalent programs in other systems. SociaLite also demonstrated competitive performance; among the compared systems, SociaLite is second fastest after Combinatorial BLAS. Most importantly, as a high-level query language, SociaLite makes it easy for users with little programming background to write many sophisticated graph applications, that are automatically optimized to run on a cluster of machines efficiently.

Keywords: Electrical Engineering.
Advisor: Lam Monica S. primary advisor. Thesis advisor
Garcia-Molina Hector advisor. Thesis advisor
Leskovec Jurij advisor. Thesis advisor
Mitchell John C. advisor. Thesis advisor
Design and implementation of The VLF wave and particle precipitation mapper sensor suite [electronic resource]

The VLF Wave and Particle precipitation Mapper (VPM) Sensor Suite will serve as a complement to ongoing DoD programs aimed at qualification of controlled precipitation of energetic electron radiation by ELF/VLF whistler-mode waves. Two benefitting programs are the Air Force Demonstration and Science Experiment (DSX) satellite mission, and the High frequency Active Auroral Research Program (HAARP). New capabilities provided by VPM are afforded by a dual detector configuration that provides sensitive measurements of energetic electrons both just-inside and just-outside the bounce loss cone, and by wave receivers with GPS-based timing facilitating interferometric measurements of electron density irregularities. The VPM sensor suite will make use of novel VLF micro-receivers consisting of radiation-hardened (up to a 2 Mrad) Low Noise Amplifier (LNA), Anti-Aliasing Filter (AAF), and Analog-to-Digital Converter (ADC) application specific integrated circuits (ASICs) developed over the past 6 years in the context of three student PhD theses. These devices provide the capability to conduct ELF/VLF observations at extremely low power and weight, while maintaining the high degree of sensitivity, resolution and dynamic range required in such measurements. Research areas of VPM will focus on determining energy spectra, temporal signatures, and spatial extent of energetic electron precipitation bursts induced by discrete whistler-mode waves, launched by ground-based sources: (i) lightning discharges, (ii) VLF transmitter signals (e.g., NPM, NAA, etc.), and (iii) ELF/VLF waves injected by modulated HF heating (i.e., HAARP). VPM will measure waves in broadband fashion so as to identify those from different sources, with high time and frequency resolution. It will simultaneously measure energetic particles with high sensitivity (large geometric factors), high time and energy resolution, so as to assess cause and affect relationships and determine calibrated theoretical models (by determining the flux levels that result from given levels of wave power density). VPM will also measure transmitted VLF wave intensity from the DSX/WIPER transmitter and determine transmitter efficiency, effective plasma sheath impedance and confirm dynamics of transmission process.

Keywords: Electrical Engineering.
Advisor: Gill John T.
Design of large scale nudge engines [electronic resource]

Congestion is a widespread problem in modern urban transportation networks; hundreds of billions of dollars are lost each year due to wasted time, extra fuel consumption, traffic accidents, etc. A significant fraction of these losses is due to peak-hour congestion on road networks, which occurs when the demand for transport exceeds capacity over a short time period each day. In this thesis, we explore the feasibility of reducing peak-hour road traffic congestion using incentives to shift drivers' commute times. We first discuss a practical implementation of such an incentive program — CAPRI (Congestion And Parking Relief Incentives). This program aimed to reduce peak-hour vehicular traffic into and out of Stanford University. Commuters who sign up for CAPRI earn points for the "good trips" they make, and these points can be redeemed for rewards (both monetary and in-kind). CAPRI also includes the capability to personalize incentives based on users' historical behavior. To complement the implementation, we develop a theoretical model for optimally reducing the cost of peak-hour congestion with targeted incentives. We study the evolution of congestion on a highway under time-varying demands using fluid models of traffic flow. We then examine the effect of shifting users' commute times on congestion. We show that ideas from the theory of optimal transport of measures can be used to develop cost-effective incentive schemes to reduce congestion. Specifically, we show that the "cost of congestion" and the "cost of nudging" are closely related to the Wasserstein distance between measures. We use this relationship to formulate linear programming problems to compute personalized recommendations and incentives to nudge drivers to the off-peak hour. We find that the resultant reduction in the cost of congestion is significant and that it helps to prioritize commuters for nudging based on their origin and destination.

Keywords: Electrical Engineering.
Advisor: Prabhakar Balaji
Johari Ramesh
Van Roy Benjamin advisor. Thesis advisor