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Filtering by: DOI 10.1128/MMBR.00049-13 Remove constraint DOI: 10.1128/MMBR.00049-13 Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • Machine learning in engineering : techniques to speed up numerical optimization

    Creator:
    Cerbone, G. (Giuseppe)
    Abstract:
    Many important application problems in engineering can be formalized as nonlinear optimization tasks. However, numerical methods for solving such problems are brittle and do not scale well. For example, these methods depend critically on choosing a good starting point from which to perform the optimization search. In high-dimensional spaces, numerical...
    Resource Type:
    Dissertation
    Full Text:
    Philosophy in Computer Science presented on April 13, 1992. Title: Machine Learning in Engineering

  • Sliding-mode control of the super maneuverable aircraft

    Creator:
    Koo, Chang Sul
    Abstract:
    In this thesis, A nonlinear methodology for the control of the highly maneuverable, high performance aircraft HARV (F-18) is studied by using sliding-mode control (SMC). This control law, which takes a continuous function when the input constraints are not considered, satisfies the reachability condition by which concerned states are driven...
    Resource Type:
    Dissertation
    Full Text:
    Computer Engineering presented on July 13, 1993. Title: Sliding-Mode Control of the Super Maneuverable

  • Physical activity recognition of free-living data using change-point detection algorithms and hidden Markov models

    Creator:
    Anderson, Michael M.
    Abstract:
    Physical activity recognition using accelerometer data is a rapidly emerging field with many real-world applications. Much of the previous work in this area has assumed that the accelerometer data has already been segmented into pure activities, and the activity recognition task has been to classify these segments. In reality, activity...
    Resource Type:
    Masters Thesis
    Full Text:
    . Anderson for the degree of Master of Science in Computer Science presented on June 13, 2013. Title

  • Offensive Direction Inference in Real-World Football Video

    Creator:
    Lu, Qingkai
    Abstract:
    Automatic analysis of American football videos can help teams develop strategies and extract patterns with less human effort. In this work, we focus on the problem of automatically determining which team is on offense/defense, which is an important subproblem for higher-level analysis. While seemingly mundane, this problem is quite challenging...
    Resource Type:
    Masters Thesis
    Full Text:
    -service used by more than 13, 000 high school, college, and professional football teams. The videos

  • Designing and understanding information retrieval systems using collaborative filtering in an academic library environment

    Creator:
    Jung, Seikyung
    Abstract:
    Accessing information on the Web has become ingrained into our daily lives, and we seek information from many different sources, including conference and journal publications, personal web pages, and others. Increasingly, web-based information retrieval systems such as web-based search engines, library on-line catalog systems, and subscription-based federated search systems are...
    Resource Type:
    Dissertation
    Full Text:
    .................................................................................................... 13 2.4.3. Document Retrieval

  • Towards reliable and survivable ocean wave energy converters

    Creator:
    Brown, Adam C.
    Abstract:
    Ocean wave energy is a new and developing field of renewable energy with great potential. The energy contained in one meter of an average wave off the coast of Newport Oregon could supply dozens of homes with electricity. However, ocean waves are usually quite irregular which leads to large bursts...
    Resource Type:
    Masters Thesis
    Full Text:
    real ocean waves. The analysis conducted in this paper used 13 years of data from the Stonewall

  • An Investigation on Nanoscale-shape-mediated Coupling Between Temperature and Densification in Intense Pulsed Light Sintering of Silver Nanoparticles

    Creator:
    Bansal, Shalu
    Abstract:
    In Intense Pulsed Light (IPL) sintering, pulsed large-area visible light from a xenon lamp is absorbed by nanoparticle films or patterns and converted to heat, resulting in rapid sintering of the nanoparticles. This work experimentally characterizes IPL sintering of silver nanoparticle films. A newly observed turning point in the evolution...
    Resource Type:
    Masters Thesis
    Full Text:
    .................................................................................... 13 2.2.1 Nanoscale Model

  • Heuristic search in symbolic probability inference

    Creator:
    Pan, Yonghong
    Abstract:
    I present a new heuristic search approach to compute approximate answers for the probability query in belief nets. This approach can compute the 'best' bounds for a query in a period of any given time (if time permitted, it will get an exact value). It inherits the essence of Symbolic...
    Resource Type:
    Capstone Project
    Full Text:
    .................................................................................................. 13 3.5. Heuristics

  • Separabilities for a new class of gray codes

    Creator:
    Park, Jung Pil
    Resource Type:
    Capstone Project
    Full Text:
    combinatorial algorithm designs [9, 12, 13), low power VLSI design [14, 15], etc. The binary reflected Gray

  • ThreshKnot: Thresholded ProbKnot for Improved RNA Secondary Structure Prediction

    Creator:
    Zhang, Liang
    Abstract:
    RNA structure prediction is a challenging problem, especially with pseudoknots. Recently, there has been a shift from the classical minimum free energy-based methods (MFE) to partition function-based ones that assemble structures based on base-pairing probabilities. Two typical examples of the latter group are the popular maximum expected accuracy (MEA) method...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.7 Comparision over families on CONTRAfold