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- Creator:
- Ding, J, Moore, TY, and Gan, Z
- Description:
- Jerboas (Jaculus jaculus) are bipedal hopping rodents that frequently transition between gaits (running, hopping, and skipping) throughout their entire speed range. It has been hypothesized that these non-cursorial bipedal gait transitions are likely to enhance their maneuverability and predator evasion ability. However, it is difficult to use the underlying dynamics of these locomotion patterns to predict gait transitions due to the large number of degrees of freedom expressed by the animals. To this end, we used empirical jerboa kinematics and dynamics to develop a unified Spring Loaded Inverted Pendulum model with defined passive swing leg motions. The simulated trajectories from the model precisely matched the experimental data. Jerboas were observed to apply different neutral swing leg angles during locomotion. By investigating the gait structure of the model with coupled and uncoupled neutral swing leg, we found two set of mechanism may explain the frequent gait transitions of jerboas.
- Keyword:
- jerboa, legged locomotion, gait transition, Legged Robots, Dynamics, Bipedal locomotion, and Non-cursorial locomotion
- Citation to related publication:
- Ding, Moore, Gan (submitted) A template model explains jerboa gait transitions across a broad range of speeds. Frontiers in Bioengineering And Biotechnology
- Discipline:
- Science and Engineering
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- Creator:
- Jones, Monica L.H.
- Description:
- This study evaluated the performance of a video-based intervention for improving the belt fit obtained by drivers. Previous laboratory studies have demonstrated that some drivers position their seat belts suboptimally. Specifically, the lap portion of the belt may be higher and farther forward relative to the pelvis than best practice, and the shoulder portion of the belt may be outboard or inboard of mid-shoulder. A video was developed to present the most important aspects of belt fit best practices, with emphasis on the lap belt. The video demonstrated how a seat belt should be routed with respect to an individual’s anatomy to ensure a proper fit. The three key belt fit concepts conveyed in the video were: 1) Lap belt low on hips, touching the thighs. 2) Shoulder belt crossing middle of collarbone. 3) Belt snug, as close to bones as possible. Additional context about the ability to achieve to good belt fit, such as opening a heavy coat or adjusting the height adjusters on the B-pillar behind the windows, were also presented.
- Keyword:
- Safety, Seatbelt Fit, Intervention, and Evaluation
- Citation to related publication:
- Jones, M.L.H., Ebert, S.M., Buckley, L., Park, J., and Reed, M.P. (2016). Evaluating an Intervention to Improve Belt Fit for Drivers. Technical Report UMTRI 2016-12. University of Michigan Transportation Research Institute, Ann Arbor, MI. , Reed, M.P., Ebert-Hamilton, S.M. and Rupp, J.D. (2012). Effects of obesity on seat belt fit. Traffic Injury Prevention, 13(4):364-372. https://doi.org/10.1080/15389588.2012.659363, Reed, M.P., Ebert, S.M. and Hallman, J.J. (2013). Effects of driver characteristics on seat belt fit. Stapp Car Crash Journal, 57:43-57. https://pubmed.ncbi.nlm.nih.gov/24435726/, and Jones, M.L.H., Ebert, S.M., and Reed, M.P. (2015). Effects of High Levels of Obesity on Driver Seat Belt Fit. Advancing Transportation Leadership and Safety Technical Report ATLAS-2015-016. University of Michigan Transportation Research Institute, Ann Arbor, MI. https://trid.trb.org/view/1427384 http://www.atlas-center.org/wp-content/uploads/2015/08/ATLAS-Final-Report-ATLAS-2016-15.pdf
- Discipline:
- Engineering
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- Creator:
- Hoffmann, Alex
- Description:
- This data contains 3 magnetometer signals of 4 noise sources. It was created to test a Underdetermined Blind Source Separation algorithm for magnetic signals.
- Keyword:
- Signal Processing, Magnetic Field, Underdetermined Blind Source Separation , UBSS, and BSS
- Discipline:
- Engineering
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- Creator:
- Brian, Chen
- Description:
- The procedure followed while creating this data is summarized in Section II of Chen, Brian, et al. "Behavioral cloning in atari games using a combined variational autoencoder and predictor model." 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2021. This data is not a result of a research but an intermediate product that is used in research. This dataset is generated to train a behavioral cloning framework from gameplay screen captures and keystrokes of an "expert" player. The RL agent that is trained using "RL Baselines Zoo package" acts as the "expert" player, whose decision making process we desire to learn. In addition to behavioral cloning experiments, this dataset is further used to demonstrate the efficacy of a novel incremental tensor decomposition algorithm on image-based data streams.
- Keyword:
- Imitation Learning, Behavioral Cloning, Reinforcement Learning, Machine Learning, and Gameplay Data
- Citation to related publication:
- Chen, Brian, et al. "Behavioral cloning in atari games using a combined variational autoencoder and predictor model." 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2021., Aksoy, Doruk, et al. "An Incremental Tensor Train Decomposition Algorithm." arXiv preprint arXiv:2211.12487 (2022)., and Chen, Brian, et al. "Low-Rank Tensor-Network Encodings for Video-to-Action Behavioral Cloning", forthcoming
- Discipline:
- Engineering and Science
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- Creator:
- Curlis, JD, Renney, TJ, Davis Rabosky, AR, and Moore, TY
- Description:
- Efficient comparisons of biological color patterns are critical for understanding the mechanisms by which organisms evolve in ecosystems, including sexual selection, predator-prey interactions, and thermoregulation. However, elongate or spiral-shaped organisms do not conform to the standard orientation and photographic techniques required for automated analysis. Currently, large-scale color analysis of elongate animals requires time-consuming manual landmarking, which reduces their representation in coloration research despite their ecological importance. We present Batch-Mask: an automated and customizable workflow to facilitate the analysis of large photographic data sets of non-standard biological subjects. First, we present a user guide to run an open-source region-based convolutional neural network with fine-tuned weights for identifying and isolating a biological subject from a background (masking). Then, we demonstrate how to combine masking with existing manual visual analysis tools into a single streamlined, automated workflow for comparing color patterns across images. Batch-Mask was 60x faster than manual landmarking, produced masks that correctly identified 96% of all snake pixels, and produced pattern energy results that were not significantly different from the manually landmarked data set. The fine-tuned weights for the masking neural network, user guide, and automated workflow substantially decrease the amount of time and attention required to quantitatively analyze non-standard biological subjects. By using these tools, biologists will be able to compare color, pattern, and shape differences in large data sets that include significant morphological variation in elongate body forms. This advance will be especially valuable for comparative analyses of natural history collections, and through automation can greatly expand the scale of space, time, or taxonomic breadth across which color variation can be quantitatively examined.
- Keyword:
- convolutional neural network, photography, sensory ecology, color evolution, vision, and image segmentation
- Citation to related publication:
- Curlis, Renney, Davis Rabosky, Moore (submitted) Batch-Mask: An automated Mask R-CNN workflow to isolate non-standard biological specimens for color pattern analysis.
- Discipline:
- Engineering and Science
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- Creator:
- Weng, Andrew, Mohtat, Peyman, Attia, Peter, Less, Greg, Lee, Suhak, and Stefanopoulou, Anna
- Description:
- The goal of this research is to investigate the impact of fast formation protocol on battery lifetime. The dataset has also been used to explore data-driven approaches in battery lifetime estimation (manuscript under review). Source code used to generate the results for this work has been included. The file contents contain a detailed README.md file which describes the organization of the files.
- Citation to related publication:
- Weng et al., Predicting the impact of formation protocols on battery lifetime immediately after manufacturing, Joule (2021), https://doi.org/10.1016/j.joule.2021.09.015
- Discipline:
- Engineering
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- Creator:
- Reed, Matthew P., Boyle, K.
- Description:
- This is the first physical anthropomorphic test device to be based both on statistical body shape models as well as 3D printing.
- Keyword:
- Child Belt Fit Manikin
- Discipline:
- Engineering
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- Creator:
- Fries, Kevin J.
- Description:
- This data is in support of the WRR paper by Fries and Kerkez: Big Ship Data: Using Vessel Measurements to Improve Estimates of Temperature and Wind Speed on the Great Lakes Code is also provided
- Keyword:
- Gaussian process regression, Data integration, Wind speed, Water surface temperature, Air temperature, and student-friendly
- Citation to related publication:
- Fries, K., and B. Kerkez (2017), Big Ship Data: Using vessel measurements to improve estimates of temperature and wind speed on the Great Lakes, Water Resour. Res., 53, 3662–3679, http://doi.org/10.1002/2016WR020084.
- Discipline:
- Engineering
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- Creator:
- BIRDS Lab, U. Michigan
- Description:
- These data were produced in an attempt to characterize the turning and steering behaviors of 1-DoF multi-legged (hexpedal in this case) robots. Such turning behaviors require sliding contact points. All the data is provided in a single, large .csv.gz file (416256 rows); additional details and example code in the README
- Keyword:
- robot, multilegged, and steering
- Citation to related publication:
- BIRDS Lab, U. BigAnt v6 robot motion tracking data - RAW dataset [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/024q-kk06, Revzen, S., & Guckenheimer, J. (2008). Estimating the phase of synchronized oscillators. Phys. Rev. E, 78, 051907. http://dx.doi.org/10.1103/PhysRevE.78.051907, and Dan Zhao and Shai Revzen 2020 Bioinspir. Biomim. 15 045001 https://doi.org/10.1088/1748-3190/ab84c0
- Discipline:
- Engineering
-
- Creator:
- BIRDS Lab, U. Michigan
- Description:
- These data were produced in an attempt to characterize the turning and steering behaviors of 1-DoF multi-legged (hexpedal in this case) robots. Such turning behaviors require sliding contact points. The .tar file contains multiple trials in .csv.gz format, with names following an informative naming convention documented in the README. Additional metadata for the trials is given in the metadata.py file in both machine and human readable form.
- Keyword:
- robot, multilegged, and steering
- Citation to related publication:
- Dan Zhao and Shai Revzen 2020 Bioinspir. Biomim. 15 045001 https://doi.org/10.1088/1748-3190/ab84c0
- Discipline:
- Engineering