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- Creator:
- Chen, Yang and Manchester, Ward IV
- Description:
- GOES_flare_list: contains a list of more than 10,000 flare events. The list has 6 columns, flare classification, active region number, date, start time end time, emission peak time, GOES_B_flare_list: contains time series data of SDO/HMI SHARP parameters for B class solar flares , GOES_MX_flare_list: contains time series data of SDO/HMI SHARP parameters for M and X class solar flares, SHARP_B_flare_data_300.hdf5 and SHARP_MX_flare_data_300.hdf5 files contain time series more than 20 physical variables derived from the SDO/HMI SHARP data files. These data are saved at a 12 minute cadence and are used to train the LSTM model., and B_HARPs_CNNencoded_part_xxx.hdf5 and M_X HARPs_CNNencoded_part_xxx.hdf5 include neural network encoded features derived from vector magnetogram images derived from the Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager (HMI). These data files typically contains one or two sequences of magnetograms covering an active region for a period of 24h with a 1 hour cadence. We encode each magnetogram with frames of a fixed size of 8x16 with 512 channels.
- Keyword:
- machine learning, data science, and solar flare prediction
- Citation to related publication:
- Chen, Y., Manchester, W., Hero, A., Toth, G., DuFumier, B. Zhou, T., Wang, X., Zhu, H., Sun, Zeyu, Gombosi, T., Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters, Space Weather, 17, 1404–1426. https://doi.org/10.1029/2019SW002214 and Jiao, Z., Chen, Y., Manchester, W. (2020). Data for Solar Flare Intensity Prediction with Machine Learning Models [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/b07j-bj08
- Discipline:
- Engineering and Science
-
- Creator:
- BIRDS Lab U. Michigan
- Description:
- This dataset contains the videos used for https://doi.org/10.7302/m05a-0d90 (the "raw" motion tracking dataset), and is intended to be unpacked into the same directory tree. The data were produced for ARO W911NF-14-1-0573 "Morphologically Modulated Dynamics" and ARO MURI W911NF-17-1-0306 "From Data-Driven Operator Theoretic Schemes to Prediction, Inference, and Control of Systems" to explore the trade-offs between various oscillator coupling models in modeling multilegged locomotion. The data were also used extensively in examining multi-contact slipping, in the studying the influence of number of legs on otherwise identical locomotion patterns, and in the use of geometric mechanics models for multilegged locomotion. Folder and file names encode the meta-data, with names following an informative naming convention documented in the README.
- Keyword:
- phase, multilegged, robot, and locomotion
- Citation to related publication:
- BIRDS Lab U. Michigan. BIRDS Lab Multipod robot motion tracking data - RAW dataset [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/m05a-0d90, Zhao, D. Ph.D. Thesis "Locomotion of low-DOF multi-legged robots" University of Michigan 2021 https://deepblue.lib.umich.edu/handle/2027.42/169985, and Zhao, D. & Revzen, S. Multi-legged steering and slipping with low DoF hexapod robots Bioinspiration & biomimetics, 2020, 15, 045001 https://doi.org/10.1088/1748-3190/ab84c0
- Discipline:
- Science and Engineering
-
- Creator:
- BIRDS Lab U. Michigan
- Description:
- These data were produced for ARO W911NF-14-1-0573 "Morphologically Modulated Dynamics" and ARO MURI W911NF-17-1-0306 "From Data-Driven Operator Theoretic Schemes to Prediction, Inference, and Control of Systems" to explore the trade-offs between various oscillator coupling models in modeling multilegged locomotion. The data were also used extensively in examining multi-contact slipping, in the studying the influence of number of legs on otherwise identical locomotion patterns, and in the use of geometric mechanics models for multilegged locomotion. Folder and file names encode the meta-data, with names following an informative naming convention documented in the README.
- Keyword:
- phase, multilegged, robot, and locomotion
- Citation to related publication:
- Zhao, D. & Revzen, S. Multi-legged steering and slipping with low DoF hexapod robots Bioinspiration & biomimetics, 2020, 15, 045001 https://doi.org/10.1088/1748-3190/ab84c0 and Zhao, D. Ph.D. Thesis "Locomotion of low-DOF multi-legged robots" University of Michigan 2021 https://deepblue.lib.umich.edu/handle/2027.42/169985
- Discipline:
- Science and Engineering