5,718 research outputs found
Towards Distributed Convoy Pattern Mining
Mining movement data to reveal interesting behavioral patterns has gained
attention in recent years. One such pattern is the convoy pattern which
consists of at least m objects moving together for at least k consecutive time
instants where m and k are user-defined parameters. Existing algorithms for
detecting convoy patterns, however do not scale to real-life dataset sizes.
Therefore a distributed algorithm for convoy mining is inevitable. In this
paper, we discuss the problem of convoy mining and analyze different data
partitioning strategies to pave the way for a generic distributed convoy
pattern mining algorithm.Comment: SIGSPATIAL'15 November 03-06, 2015, Bellevue, WA, US
Computational structured illumination for high-content fluorescent and phase microscopy
High-content biological microscopy targets high-resolution imaging across
large fields-of-view (FOVs). Recent works have demonstrated that computational
imaging can provide efficient solutions for high-content microscopy. Here, we
use speckle structured illumination microscopy (SIM) as a robust and
cost-effective solution for high-content fluorescence microscopy with
simultaneous high-content quantitative phase (QP). This multi-modal
compatibility is essential for studies requiring cross-correlative biological
analysis. Our method uses laterally-translated Scotch tape to generate
high-resolution speckle illumination patterns across a large FOV. Custom
optimization algorithms then jointly reconstruct the sample's super-resolution
fluorescent (incoherent) and QP (coherent) distributions, while digitally
correcting for system imperfections such as unknown speckle illumination
patterns, system aberrations and pattern translations. Beyond previous linear
SIM works, we achieve resolution gains of 4x the objective's
diffraction-limited native resolution, resulting in 700 nm fluorescence and 1.2
um QP resolution, across a FOV of 2x2.7 mm^2, giving a space-bandwidth product
(SBP) of 60 megapixels
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