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

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  • Usable and Scalable Querying of Scientific Datasets

    Creator:
    McCamish, Benjamin J.
    Abstract:
    Scientists and engineers have to analyze and query multiple large databases. Analysis over databases created by phasor measurement units can provide insight into the health of the grid, thereby improving control over operations. Realizing this data-driven control, however, requires validating, processing and storing massive amounts of PMU data efficiently, which...
    Resource Type:
    Dissertation
    Full Text:
    committee: Alan Fern, David Maier, and Kyle Niemeyer. I would also like to thank my peers for their

  • Representationally Robust and Scalable Learning over Relational Databases

    Creator:
    Picado Leiva, Jose Manuel
    Abstract:
    Learning novel concepts from relational databases is an important problem with applications in several disciplines, such as data management, natural language processing, and bioinformatics. For a learning algorithm to be effective, the input data should be clean and in some desired representation. However, real-world data is usually heterogeneous – the...
    Resource Type:
    Dissertation
    Full Text:
    : Alan Fern, David Maier, Prasad Tadepalli, and Hector Vergara. Their insightful comments helped this

  • Large-Area Nanoplasmonic Structures for Enhanced Fluorescence-Based Biosensing

    Creator:
    Wang, Yi-Chieh
    Abstract:
    An innovative silver nano-dimple arrays (Ag DAs)-integrated microfluidic device was developed to achieve highly sensitive fluorescence-based nucleic acid detection. The Ag DAs were utilized to produce surface plasmon resonance (SPR) for strong fluorescence enhancement. We systematically investigated the plasmon-enhanced fluorescence by controlling the nanostructure dimension of the Ag DA substrate....
    Resource Type:
    Masters Thesis

  • Collaborative Online Learning For Join Processing

    Creator:
    Xie, Mian
    Abstract:
    Relational binary operators, such as join, are arguably the most costly and frequently used operations in relational data systems. In many join algorithms, the majority of the process time is spent on scanning and attempting to join the parts of the relations that do not satisfy the join condition and...
    Resource Type:
    Capstone Project

  • Learning to Estimate Multi-Relation Aggregation Functions

    Creator:
    Jadhav, Rashmi Suresh
    Abstract:
    Multi-relation aggregation queries process the join operator before computing the aggregation function. This join is arguably the most costly operation since traditional join algorithms spend majority of their time trying to join the parts of the relations that do not generate any output tuples. This causes slow response times with...
    Resource Type:
    Masters Thesis

  • Relational Learning over Dirty Data Using Data Constraints

    Creator:
    Lee, Ga Young
    Abstract:
    Real-world datasets are dirty and contain many errors. Examples of these issues are violations of integrity constraints, duplicates, and inconsistencies in representing data values and entities. Applying machine learning on dirty databases may lead to inaccurate results. Users have to spend a lot of time and effort repairing data errors...
    Resource Type:
    Masters Thesis

  • Plasmonic Nano-Antenna and Modulator for On-Chip Optical Interconnects

    Creator:
    Gao, Qian
    Abstract:
    With the rapid growth of worldwide internet traffic in data centers and clouds, silicon photonics has been utilized to provide enormous data bandwidth and outstanding energy efficiency over electronics. Computing servers and storage servers that are connected by communication links are relying more on optical rather than electrical means mainly...
    Resource Type:
    Dissertation

  • Variations Foraging

    Creator:
    Srinivasa Ragavan, Sruti
    Abstract:
    Information Foraging Theory (IFT) has successfully explained how people seek information in various domains, in turn, informing the design of several tools and information-intensive environments. However, prior research has not explored foraging in the presence of several, very similar variants of the same artifact. Such variants are commonplace in several...
    Resource Type:
    Dissertation
    Full Text:
    , Dr. Anita Sarma, Dr. Cindy Grimm, Dr. Eric Walkingshaw and Dr. David Kling for all their feedback

  • Quantum dot plasmon coupling : Fundamental study and applications

    Creator:
    Kannegulla, Akash
    Abstract:
    The dissertation focuses on the engineering of light-matter interaction using plasmonic nanoparticles and metamaterials to achieve enhanced luminescence and based on which to improve the performance of biosensing and light-emitting technologies. We designed and fabricated a spectrum of nanostructures to exhibit particular dispersion relations capable of controlling the spontaneous emission...
    Resource Type:
    Dissertation

  • Part-based and Uncertainty-Aware Few-shot Object Segmentation in Images

    Creator:
    Nguyen, Khoi D.
    Abstract:
    This dissertation addresses few-shot object segmentation in images. The goal of segmentation is to label every image pixel with a class of the object occupying that pixel, where the class may represent a semantic object category or instance. In few-shot segmentation, training and test datasets have different classes. Every new...
    Resource Type:
    Dissertation