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How Citizen Scientists are Monitoring Global Meteor Shower Activity with Machine Learning Open Source Research: Siddha Ganju at the OAE's 3rd Shaw-IAU Workshop

Authors: Ganju, Siddha;

How Citizen Scientists are Monitoring Global Meteor Shower Activity with Machine Learning Open Source Research: Siddha Ganju at the OAE's 3rd Shaw-IAU Workshop

Abstract

Citizen scientists have automated the Cameras for Allsky Meteor Surveillance (CAMS) data network, so data is automatically downloaded from the cameras, prepped for triangulation, and analyzed. Additionally, an ML algorithm replicates the scientists thought process to sift through the video captured each night to identify meteor showers with results published on the NASA CAMS Meteor Shower Portal. The open source portal not only aids in effective communication of ideas and results to a diverse audience but is a useful interactive educational tool used to explore meteor shower activity from the previous night globally and encourages citizen scientists to develop an interest in space science. Learn how to reuse the open source code for your datasets and explore meteor showers!

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Astronomy Education

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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