Internet of the ocean

An octopus swims against a black background

UW scientists unravel the ocean’s mysteries with cloud computing, data science skills, and a sea of data.

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How to discover asteroids with algorithms

Figure 1: Visualization of asteroids in the Solar System’s main Asteroid Belt. The circles represent the orbits of Mercury, Venus, Earth, Mars and Jupiter (see this animation on YouTube by Alex Parker).

Researchers have recently presented a new algorithm named THOR (for “Tracklet-less Heliocentric Orbit Recovery”) which employs coordinate transformations and clustering techniques to reduce the number of combinations needed to be tested to computationally tractable levels.

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Community Snow Observations

Figure 1: Fiona Hill, Josie Hill, and Tessa Hill use a tape measure and ski pole to measure the snow depth in Mazama, Washington. Photo credit: David Hill

Citizen scientists collect snow data and submit it along with their location to a smartphone application; the data are then used to by scientists to check the accuracy of other regional snow datasets and model simulations.

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nbdocker = Jupyter + Docker: simplifying reproducible research

nbdocker graphic

nbdocker is an extension to Jupyter that allows the embedding of Docker containers within notebooks. This allows the mix and match of different computing environments and programming languages.

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Observing the cosmic dawn

HERA, under construction in 2018

We have developed one of the world’s most precise data analysis software suites to achieve the unprecedented spectral-spatial dynamic range needed to see the first stars and galaxies.

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Fake profiles detection on online social networks

Graphic, Springer.com

A team of researchers, including Michael Fire, UW eScience Institute postdoctoral research fellow, has developed a machine learning solution to detect fake users on social networks. The research uses a generic unsupervised algorithm to improve the safety of these networks.

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Shifts in marine microbial populations detected using statistical machine learning

Coverage of the SeaFlow data used in the change-point analysis. Black lines denote individual research cruise tracks and the heat-map shows the estimated quantity of chlorophyll at each spatial location based on satellite data.

The SeaFlow cytometer continuously profiles microbial populations across thousands of kilometers of the ocean surface during research cruises. The ‘multiple change-point detection’ method, developed by a UW team including eScience affiliates, can detect changes in scatter and fluorescence properties in these large datasets within seconds by using a dynamic programming algorithm.

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