Browsing by Author "Glesener, Lindsay"

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    Model file for Ishikawa et al. "Automatic Detection of Occulted Hard X-ray Flares Using Deep-Learning Methods" in Sol. Phys. (2021)
    (2021) Ishikawa, Shin-nosuke; Matsumura, Hideaki; Uchiyama, Yasunobu; Glesener, Lindsay
    Deep-learning model for occulted hard X-ray flare detection was published in association with the publication Ishikawa et al. "Automatic Detection of Occulted Hard X-ray Flares Using Deep-Learning Methods" in Sol. Phys. (2021). We checked the model file with the Google Colaboratory environment (Python 3.6.9 and Tensorflow 2.4.0).
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    Signal of Opportunity Time Difference of Arrival Estimation Using Adaptive Filtering Techniques
    (2017 IEEE Aerospace Conference, 2017) Runnels, Joel T.; Gebre-Egziabher, Demoz; Glesener, Lindsay
    EXACT and SOCRATES are a pair of CubeSats being developed to advance the TRL of a dual-use sensor. It can function either as x-ray detector used for characterization of high energy photons or as a sensor for measuring relative ranges between users in deep space operations. The ranging function of the sensor is described in this paper. After describing the measurements generated by the sensor, the algorithms that make use of this information to generate a position solution are presented. As a validation case study, data from the Japanese spacecraft Suzaku’s observation of the Crab Nebula Pulsar is used to estimate the spacecraft’s change in position along the line-of-sight to the pulsar, using this estimation scheme. Suzaku’s observations are suitable for this application because the spacecraft's Hard X-Ray Detector (HXD) is similar in effective surface area to the prototype X-Ray/gamma-ray detector currently under development for use onboard EXACTand SOCRATES. Thus, validation of this technique using data from Suzaku serves to verify the feasibility of this navigation technique onboard other spacecraft with detectors of similar size.
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    Solar Jet Hunter: Jet Catalog from HEK Events 2011-2016
    (2023-09-25) Musset, Sophie; Sankar, Ramanakumar; Lasko, Kekoa; Jol, Paloma; Glesener, Lindsay; Fleishman, Gregory; Panesar, Navdeep; Zhang, Yixian; Hurlburt, Neal; Fortson, Lucy; Ostlund, Erik; Alnahari, Suhail; Jeunon, Mariana; Kapsiak, Charles; glesener@umn.edu; Glesener, Lindsay; UMN Space Physics Group
    This database constitutes the first release of data from the Solar Jet Hunter project. Solar Jet Hunter is a Zooniverse-based citizen science project that has, since 2021, enlisted volunteers from the general public to help identify extreme ultraviolet jets of plasma in the Sun’s corona. These jets release magnetic energy at the Sun and enable streams of plasma and energetic particles to escape to the solar system, but the origins of and mechanisms underlying these jets are still not understood. In Solar Jet Hunter, videos of possible jets are presented to volunteers, who are asked to identify whether a jet is present, and if so, its start time, end time, and base location. Volunteers also box the jet, providing information on its shape and height over time. The results from many volunteers are then aggregated into consensus results for each potential jet in the study. Those results are listed in this data set. The data presented to volunteers is from the Solar Dynamic Observatory / Atmospheric Imaging Assembly instrument, specifically the 304 angstrom filter, and all of the candidate jets were identified as possible jets in the Heliophysics Event Knowledgebase (HEK). The data set included here lists Solar Jet Hunter results from the years 2011 through 2016.