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in the generation of an unprecedented quantity of data. This marks an inexorable shift of the field into the realm of “big data,” necessitating the development of novel machine learning approaches
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are published in this field every year, and the publication rate is constantly increasing. The large number of data sources in combination with a wide variety of industrially important chemicals and associated
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cycle mass spectrometers have made this analysis possible, there are still looming problems related to the inherently large search space and to comparing results temporally or between laboratories
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supports US Semiconductor Manufacturing in overcoming various qualitative and quantitative measurement challenges especially over large areas, as is needed for effective manufacturing process control
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or poor state-of-knowledge surrounding nuclear input data. Large uncertainties on half-lives limit the precision of geological and astrophysical clocks. Imprecise or inaccurate beta spectrum shapefactors
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differentiation, data describing the changes in gene expression at the single cell level are needed. In this project, quantitative live cell imaging and image analysis will be used to follow gene expression
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clocks used in the past, creating “gappy” data which often strain, or outright violate, the assumptions underlying the statistical models currently used. This project centers around investigating and
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301.975.4579 Description As the demand for high resolution, high content imaging increases, the cost and challenges of acquiring, storing, processing, and analyzing today’s very large imaging data sets are even
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on interdisciplinary approaches to address the current barriers and bottlenecks in these fields including (1) advanced statistical, bioinformatic, and chemometric analyses of large-scale data; (2) chemical annotation
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nanodiamond, which is the objective of this work. A unified theory for lattice defects in nanodiamonds is a challenging problem because the nanodiamonds can be too small or too big for a conventional