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Filtering by: Creator Hanes, David Fink Remove constraint Creator: Hanes, David Fink Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • A methodology to enable wind farm automatic generation control

    Creator:
    Han, Hai-Yue
    Abstract:
    Over the last decade the increase in penetration of wind power and its variable nature has begun to add considerable stress to and threatened the stability of the nation's grid. In order to continue growth wind farms will need to have the ability to participate in the same grid frequency...
    Resource Type:
    Dissertation
    Full Text:
    appreciation to his committee members Dr. Ean Amon, Dr. David Hackleman and Roger Traylor for their time and

  • Efficient Algorithms for Robust Spatiotemporal Data Analysis

    Creator:
    Moore, Travis W.
    Abstract:
    Many large-scale data analysis applications involve data that can vary over both time and space. Often the primary goal of analyzing spatiotemporal data is identifying trends, movements, and sudden changes with respect to time, location, or both. This can include a variety of applications in economics (housing prices, unemployment, job...
    Resource Type:
    Dissertation
    Full Text:
    , Max Larrivee, Jeffrey Oliver and Jeremy Kerr) and eBird (Daniel Fink, Chris Wood, and Frank La Sorte

  • Machine learning for improving the quality of citizen science data

    Creator:
    Yu, Jun
    Abstract:
    Citizen Science is a paradigm in which volunteers from the general public participate in scientific studies, often by performing data collection. This paradigm is especially useful if the scope of the study is too broad to be performed by a limited number of trained scientists. Although citizen scientists can contribute...
    Resource Type:
    Dissertation
    Full Text:
    distribution of Western Meadowlark across the western United States in June 2009. We thank Daniel Fink for

  • Species Distribution Modeling of Citizen Science Data as A Classification Problem with Class-Conditional Label Noise

    Creator:
    He, Liqiang
    Abstract:
    Species distribution models (SDM), which quantify the correlation between the distribution of a species and environmental factors, are increasingly used to map and monitor animal and plant distributions in the context of awareness of environmental change and its ecological consequence. For perfect data, this is a straightforward classification problem from...
    Resource Type:
    Masters Thesis

  • Predicting activity type from accelerometer data

    Creator:
    Zheng, Yonglei
    Abstract:
    The study of physical activity is important in improving people’s health as it can help people understand the relationship between physical activity and health. Accelerometers, due to its small size, low cost, convenience and its ability to provide objective information about the frequency, intensity, and duration of physical activity, has...
    Resource Type:
    Masters Thesis

  • Extending the TekBots [superscript TM] Platform for Learning [superscript TM] to upper division ECE courses

    Creator:
    Smit, Adriaan
    Abstract:
    In April of 1997 it was pointed out at an NSF Engineering Education Innovators conference that “… education appears to ignore the need for connections and for integration – which should be at the core of an engineering education.” In order to solve this problem a group named ‘TekBotsTM’ was...
    Resource Type:
    Masters Thesis

  • A Generation Prioritization Method for Power System Restoration with Renewable Resources

    Creator:
    Mate, Adam
    Abstract:
    The electrical grid is a key component of the Nation's critical infrastructure. Its continuous and reliable operation is of vital importance; any system-wide disruption would have a debilitating impact on crucial services, public health and safety, the economy, and the national security of the United States. High-impact low-frequency events pose...
    Resource Type:
    Dissertation
    Full Text:
    of the Halloween GMD event. Mother Eva Matene Kovacs, father Zsolt Mate, and brother David Mate, for

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation

  • Machine Learning Techniques to Model Species Interactions and Distributions Under Imperfect Detection

    Creator:
    Seo, Eugene
    Abstract:
    Ecological domains seeking to understand the environment and the behavior of species have received little attention in machine learning (ML), despite the fact that environmental changes have a significant impact on humans as well as ecosystems. Some ecological problems can be formulated similarly to other common ML applications, but there...
    Resource Type:
    Dissertation