Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"data pipelines"”.
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Uncertainty Quantification in Security Aware Data Pipelines
… systems, the diversity and volume of data have expanded. Proper management of sensitive information collected and processed through data pipelines is crucial. Traditional data pipelines usually perform error analysis of the final pipeline output after a detection model. As a result, …
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SenseML : a platform for constructing IOT data pipelines
… platform that enables users to transform sensor data from the IOT domain into a machine learning-ready format - what we call an attribute time series. It is a cloud-based platform that can process signals using user-specified functions. It offers users immense flexibility in integrating functions …
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Components and principles of streaming principal components
… Analysis (PCA) is a fundamental pillar of modern data pipelines, but its traditional implementation is woefully inadequate for modern data problems. In this work we present our contributions to the field of streaming principal component analysis---research that adds critical flexibility to one of …
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Parallel and Distributed Just-in-Time Shell Script Compilation
… storage systems to efficiently execute data-processing pipelines. Distributed-PaSh analyzes the dataflow graph of a given script to create highly parallel data pipelines and execute those pipelines in a distributed cluster while giving special attention to data locality and movement. …
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The Development and Deployment of Sensors and Algorithms for the Mobile Monitoring of Urban Surface Water Quality
… quality within the Amsterdam canal network. The data provide encouraging evidence that opportunistic measurements from a small number of mobile platforms can enable high-resolution mapping and can be used to improve modeling and control of water quality across the city. In the second and third …
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Interpretable Machine Learning Methods for Landslide Analysis
… and difficult to survey. We combat the resulting data sparsity by carefully designing learning tasks and data pipelines for detection and susceptibility. We meaningfully extract 20 features with scientific or computational basis. We then provide a comprehensive evaluation of four different machine …
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Quantifying phytoplankton biomass and sediment in river plumes along the Agulhas Bank using remotely sensed data with deep learning techniques
… has encouraged the use of remotely sensed data obtained from satellites. Remote sensing capabilities have advanced over the past few decades, along with increased computational efficiency, and sizeable open-access data pipelines. However, current satellite data products are not always …
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SUPPORTING COMPANIES IN THEIR DIGITAL TRANSITION TO SMART MANUFACTURING SYSTEMS
… to keep not only design, but also production data in-house, to protect industrial secrets, prevents the export of production or design data to external cloud services. Second, the need to keep using specially tailored legacy machines, which are not I4.0 compliant by design, leads to the lack …
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The complexity of bioinformatics: techniques for addressing the combinatorial explosion in proteomics and genomics
The last decade has seen an explosion of data arising from the development and proliferation of high-throughput data gathering and analysis pipelines. In order to transform this data into useful hypotheses and conclusions, it is necessary to determine which of it is pertinent to the problem being …