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Electrical Engineering and Computer Sciences - Master's degree

Mostrando recursos 1 - 20 de 5.871

  1. Plasma oxidation of silicon : kinetics studies

    Chan, David Tai Wai
    by David Tai Wai Chan.

  2. Transfer learning for predictive models in MOOCs

    Boyer, Sebastien (Sebastien Arcario)
    Predictive models are crucial in enabling the personalization of student experiences in Massive Open Online Courses. For successful real-time interventions, these models must be transferable - that is, they must perform well on a new course from a different discipline, a different context, or even a different MOOC platform. In this thesis, we first investigate whether predictive models "transfer" well to new courses. We then create a framework to evaluate the "transferability" of predictive models. We present methods for overcoming the biases introduced by specific courses into the models by leveraging a multi-course ensemble of models. Using 5 courses from...

  3. Understanding the institutional landscape of cyber security

    Testart Pacheco, Cecilia Andrea
    The decentralized architecture of the Internet, which has been key to its development and worldwide deployment, is making it challenging to secure Internet user experience. Many organizations claim to be playing a role in improving Internet security. If anything, the space of security-related institutions seems on first inspection to be over-populated, yet poor security persists. This work proposes a framework to understand the role different institutions play in cyber security. The analysis gives insights into the broad institutional ecosystem of public, private and international actors, and the varied nature of these institutions, their interests, incentives, and contributions to cyber security...

  4. Studies of correlation functions in random medium theory by Son V. Nghiem.

    Nghiem, Son V. (Son Van)
    Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1988.

  5. An integrated model of flight and passenger delay for policy analysis in the National Air Transportation System

    Sun, He, S.M. Massachusetts Institute of Technology
    Demand for air travel has increased over the years and so have airport delays and congestion. Delays have a huge impact on airline costs and influence the satisfaction of passengers, thus becoming an important topic of research in the field of air transportation. In recent literature, a Passenger Delay Calculator (PDC) was proposed to estimate passenger delays. The PDC computes passenger delays for a specified day based on actual flight schedules, fight cancellation information, and ticket booking information. However, since actual fight schedules are a necessary input, the PDC cannot be applied directly to hypothetical scenarios, in which different cancellation...

  6. Quantifying the impact of care team discontinuities on medically unnecessary delays in inpatient flow

    Johnston, Andrew Thomas, S.M. Massachusetts Institute of Technology
    This thesis quantifies the impact of clinical care team discontinuities on inpatient length-of-stay (LOS) and admission wait time within Massachusetts General Hospital's Department of Medicine (DOM). The DOM is the hospital's largest clinical department by inpatient volume and supports a highly diverse patient population. Like many Academic Medical Centers, the DOM is confronted with increasing inpatient volume (>5% annual growth) and is showing symptoms of being capacity constrained, including rising patient wait times for admission from the Emergency Department. With the goal of informing specific interventions to increase patient throughput, this study evaluates the impact of end-of-rotation Attending physician handoffs...

  7. Object localization and identification for autonomous operation of surface marine vehicles

    Mentzelos, Konstantinos
    A method for autonomous navigation of surface marine vehicles is developed A camera video stream is utilized as input to achieve object localization and identification by application of state-of-the-art Machine Learning algorithms. In particular, deep Convolutional Neural Networks are first trained offline using a collection of images of possible objects to be encountered (navy ships, sail boats, power boats, buoys, bridges, etc.). The trained network applied to new images returns real-time classification predictions with more than 93% accuracy. This information, along with distance and heading relative to the objects taken from the calibrated camera, allows for the precise determination of...

  8. Urban computing using call detail records : mobility pattern mining, next-location prediction and location recommendation

    Leng, Yan, S.M. Massachusetts Institute of Technology
    Urban computing fuses computer science with other fields, such as transportation, in the context of urban spaces by connecting ubiquitous sensing technologies, analytical models and visualizations to solve challenging problems in urban environment and operation systems. This paper focuses on Call Detail Records, one widely collected opportunistic sensing data source for billing purposes, to understand presence patterns, develop mobility prediction methods and reduce traffic congestions with location recommendations. Understanding human mobility and presence patterns at locations are the building blocks for behavior prediction, service design and system improvements. In the first part, this thesis focuses on 1) understanding presence patterns...

  9. Constrained extended Kalman filter : an efficient improvement of calibration for dynamic traffic assignment models

    Zhang, Haizheng, S.M. Massachusetts Institute of Technology
    The calibration (estimation of inputs and parameters) for dynamic traffic assignment (DTA) systems is a crucial process for traffic prediction accuracy, and thus critical to global traffic management applications to reduce traffic congestion. In support of the real-time traffic management, the DTA calibration algorithm should also be online, in terms of: 1) estimating inputs and parameters in a time interval only based on data up to that time; 2) performing calibration faster than real-time data generation. Generalized least squares (GLS) methods and Kalman filter-based methods are proved useful in online calibration. However, in literature, the road networks selected to test...

  10. The economics of cryptographic trust : understanding certificate authorities

    Specter, Michael Alan
    Certificate Authorities (CAs) play a crucial role in HTTPS, the mechanism that secures all of the web's most important communication; if it has a log-in page, it must use HTTPS. However, recent history is littered with instances of CAs unabashedly undermining the trust model of the web in favor of economic gain, causing catastrophic harm to users in the process. The purpose of this thesis is to understand how well user, domain owner, and browser vendor controls function in order to evaluate methods of realigning CA incentives. Using a compendium of past incidents of CA failure as a series of...

  11. An investigation into the utility of second differentiation of sound frequency spectra for speech analysis

    Koogle, Jay Franklin
    by Jay Franklin Koogle.

  12. Magnetometry with ensembles of nitrogen vacancy centers in bulk diamond

    Teale, Carson (Carson Arthur)
    This thesis summarizes experiments conducted to develop a high sensitivity vector magnetometer using nitrogen vacancy (NV) centers in a bulk diamond sample. This project began by analyzing the sensitivity of a single NV orientation using a continuous wave electron spin resonance approach. A protocol for determining the diamond's orientation was developed to map vector magnetic field readings in the diamond reference frame to the lab frame. Preliminary vector field measurements and differential vector measurements were performed. Although these showed promising results, significant instrument and ambient magnetic noise limited the achievable sensitivity. A new frequency locking measurement technique was developed to...

  13. Wide-field magnetic field imaging with nitrogen vacancy centers in nanodiamonds at high frame-rates

    Foy, Christopher, S.M. Massachusetts Institute of Technology
    The nitrogen vacancy center (NV) is a promising single spin system in diamond with optical polarization, readout and optically detected magnetic resonances (ODMR). The NV has been shown to be a sensitive magnetometer at room temperature. In particular, owing to their small size, NV centers in nanocrystals (nanodiamonds) offer magnetic field imaging with high spatial resolution. Competitive magnetic field imaging methods such as magnetic force microscopy (MFM) or superconducting quantum interference devices (SQUID) either image serially, and are thus slow, or are limited in their use for biological systems. Nanodiamonds in contrast have the advantage that they can be attached...

  14. Inferring the properties of transcription factor regulation

    Grzadkowski, Michal R
    The regulatory targets of transcription factors are costly to directly detect using existing technologies. Many computational models have thus been developed to infer the genes targeted by TFs using gene expression profiles, position weight matrices modeling TF protein binding, histone modifications, and other secondary datasets. We develop a framework for scoring the potential targets of various TFs using models that take the profile of motif hits on the proximity of transcription start sites as input, and describe methods to validate this framework using expression datasets. These models are then extended to include cis-regulatory regions inferred from epigenetic data.

  15. Vuvuzela : scalable private messaging that hides metadata

    Lazar, David, S.M. Massachusetts Institute of Technology
    Private messaging over the Internet has proven challenging to implement, because even if message data is encrypted, it is difficult to hide metadata about who is communicating in the face of traffic analysis. Systems that offer strong privacy guarantees, such as Dissent [39], scale to only several thousand clients, because they use techniques with superlinear cost in the number of clients (e.g., each client broadcasts their message to all other clients). On the other hand, scalable systems, such as Tor, do not protect against traffic analysis, making them ineffective in an era of pervasive network monitoring. Vuvuzela is a new...

  16. Comprehensive geometric modeling of human cerebral vasculature for quantitative vascular analysis

    Linghu, Changyang
    In this work we developed a comprehensive and structured geometric model of human cerebral vasculature for quantitative anatomical analysis. We first proposed a general and structured geometric representation of the interconnected vascular network as a framework. We then described an image processing pipeline for the segmentation of vascular anatomy from discrete scalar field images, and applied the pipeline to segment the anatomical structures of cerebral vasculatures from whole brain magnetic resonance angiography (MRA) scans of healthy adult subjects. Next, we employed the proposed geometric representation to generate the comprehensive geometric model of human cerebral vasculature from those segmented anatomies. In...

  17. Sublinear-time algorithms for counting star subgraphs with applications to join selectivity estimation

    Peebles, John Lee Thompson, Jr
    We study the problem of estimating the value of sums of the form ... when one has the ability to sample xi ;> 0 with probability proportional to its magnitude. When p = 2, this problem is equivalent to estimating the selectivity of a self-join query in database systems when one can sample rows randomly. We also study the special case when {x} is the degree sequence of a graph, which corresponds to counting the number of p-stars in a graph when one has the ability to sample edges randomly. Our algorithm for a ...-multiplicative approximation of Sp has query...

  18. Reinforcement learning with natural language signals

    Sidor, Szymon
    In this thesis we introduce a technique that allows one to use Natural Language as part of the state in Reinforcement Learning. We show that it is capable of solving Natural Language problems, similar to Sequence-to-Sequence models, but using multistage reasoning. We use Long Short-Term Memory Networks to parse the Natural Language input, whose final hidden state is used to compute action scores for the Deep Q-learning algorithm. First part of the thesis introduces the necessary theoretical background, including Deep Learning approach to Natural Language Processing, Recurrent Neural Networks and Sequence-to-Sequence modeling. We consider two case studies: translation and dialogue....

  19. A systems approach to software security in aviation

    Helfer, Jonas
    Field Loadable Software in commercial aviation is indispensable for vital avionics functions yet its security has never been studied in depth. Due to the recent introduction of wireless software loading capabilities and Internet-connected in-flight entertainment systems along with several high-profile information security breaches in other sectors, the security of Field Loadable software has come under closer scrutiny. Conventional information systems security analysis approaches focus on finding and preventing vulnerabilities in the implementation of a system, but they are not designed to include the organizational "soft" components of a system. The aim of this thesis is to provide a comprehensive security...

  20. Authentication protocol using trapdoored matrices

    Sotiraki, Aikaterini
    In this thesis, we propose a new type of public-key authentication protocol, which is based on timing gaps. The honest user's secret key allows him to perform a task faster than any adversary. In our construction, the public key is a n x n matrix and the secret key is a trapdoor of this matrix. The task which an honest user has to perform in order to authenticate himself is a matrix-vector multiplication, where the vector is supplied by the verifier. We provide specific constructions of the trapdoor and analyze them both theoretically and practically.

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