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- Creator:
- Zhou, Lingxiao
- Description:
- A work that demonstrates enhancement by nearly two-orders of magnitude of the circular-polarized optical Stark effect in WSe₂ embedded into a Fabry Perot cavity, and use this mechanism to implement a XOR switch.
- Keyword:
- Nonlinear optics and Photonics
- Citation to related publication:
- Lingxiao Zhou, et al. Cavity-Floquet Engineering. Nature Communication (2024)
- Discipline:
- Science and Engineering
-
- Creator:
- Urs, Karthik, Carlson, Jessica, Srinivas Manohar, Aditya, Rakowiecki, Michael, Alkayyali, Abdulhadi, Saunders, John E., Tulbah, Faris, and Moore, Talia Y.
- Description:
- Robotic models are useful for independently varying specific features, but most quadrupedal robots differ so greatly from animal morphologies that they have minimal evolutionary relevance. Commercially available quadrupedal robots are also prohibitively expensive for biological research programs and difficult to customize. Here, we present a low-cost quadrupedal robot with modular legs that can match a wide range of animal morphologies for biomechanical hypothesis testing. The Robot Of Theseus (TROT) costs ≈$4000 to build out of 3D printed parts and standard off-the-shelf supplies. Each limb consists of 2 or 3 rigid links; the proximal joint can be rotated to become a knee or elbow. Telescoping mechanisms vary the length of each limb link. The open-source software accommodates user-defined gaits and morphology changes. Effective leg length, or crouch, is determined by the four-bar linkage actuating each joint. The backdrivable motors can vary virtual spring stiffness and range of motion.
- Keyword:
- Robo-physical model, quadruped, locomotion, morphology, and biomechanics
- Citation to related publication:
- Urs, Carlson, Srinivas Manohar, Rakowiecki, Alkayyali, Saunders, Tulbah, Moore. (forthcoming) The Robot of Theseus: A modular robotic testbed for legged locomotion.
- Discipline:
- Engineering
-
- Creator:
- Herzog, Joshua M, Verkade, Angela, and Sick, Volker
- Description:
- Data deposited here includes 60 image sets (30 individual participants, and 2 eyes per individual) consisting of raw fluorescence images, diffuse reflection images using ambient lighting, images used for correction, and calibration, and metadata. Images are split into two wavelength bands as described in the methodology. Raw images are stored in Hierarchical Data Format 5 (HDF5) file nodes (one file per eye) and each image node contains a tag for frame rate, exposure duration, and timestamp (stored in ImageData.zip). Summary statistics including demographic data, participant-reported diseases (e.g., diabetes, keratoconus), and pupil size are also stored in a text-based comma-separated table and as an Excel spreadsheet. Finally, 2-channel pseudocolor images and ratiometric grayscale images combining the two fully-processed image bands are stored as portable network graphics (PNG) files (stored in PseudocolorImages.zip).
- Keyword:
- Fluorescence, Imaging, Ocular lens, Corneal disease, Cataract, and Diabetes
- Citation to related publication:
- Herzog, Joshua M., Verkade, Angela, and Sick, Volker. "Corneal shadowgraphy: a simple, low-cost, rapid, and quantitative tool with potential clinical utility." Manuscript in review. 2024. and Herzog, Joshua M., Verkade, Angela, and Sick, Volker. "Quantitative and rapid in vivo imaging of human lenticular fluorescence." Manuscript in review. 2024.
- Discipline:
- Health Sciences and Engineering
-
- Creator:
- El Shair, Zaid A., Abu-raddaha, Abdalmalek , Cofield, Aaron, Alawneh, Hisham, Aladem, Mohamed, Hamzeh, Yazan, and Rawashdeh, Samir A.
- Description:
- The SID dataset was curated to support advanced research in autonomous driving systems, particularly focusing on perception under adverse weather and lighting conditions. This dataset encompasses over 178k high-resolution stereo image pairs organized into 27 sequences, reflecting a rich variety of conditions such as snow, rain, fog, and low light. It covers dynamic changes in driving scenarios and environmental backgrounds, including university campuses, residential streets, and urban settings. The dataset is designed to challenge perception algorithms with scenarios such as partially obscured camera lenses and varying visibility, promoting the development of robust computer vision models. No specialized software or scripts are necessary for accessing the image data, as the files are provided in standard PNG format. However, researchers and developers may require their image processing and computer vision toolkits to utilize the dataset effectively in their work.
- Keyword:
- Autonomous Driving, Adverse Weather, Stereo Vision, Image Dataset, Computer Vision, and Perception Algorithms
- Citation to related publication:
- El-Shair, Z.A., Abu-raddaha, A., Cofield, A., Alawneh, H., Aladem, M., Hamzeh, Y., and Rawashdeh, S.A., 2024. SID: Stereo Image Dataset for Autonomous Driving in Adverse Conditions. In 2024 IEEE National Aerospace and Electronics Conference (NAECON). IEEE. In press.
- Discipline:
- Engineering
-
- Creator:
- Marks, Thomas A and Gorodetsky, Alex A
- Description:
- WarpX simulations of the 2D axial-azimuthal Hall thruster benchmark, as described in IEPC paper 409 (2024): https://www.thomasmarks.space/files/Marks_T_IEPC_2024_WarpX.pdf Contains one subdirectory: baseline_20us: 20 us of data, saved every 5000 iterations (32 GB) The data is in AMReX plotfile format.
- Keyword:
- hall thruster, plasma, pic, particle in cell, particle, cell, kinetic, electric propulsion, and thruster
- Citation to related publication:
- @inproceedings{marksWarpX2024, title = {Hall thruster simulations in {{Warp-X}}}, booktitle = {38th {{International Electric Propulsion Conference}}}, author = {Marks, Thomas A. and Gorodetsky, Alex A.}, year = {2024}, month = jun, address = {Toulouse, France} }
- Discipline:
- Engineering
-
- Creator:
- El Shair, Zaid A. and Rawashdeh, Samir A.
- Description:
- The MEVDT dataset was created to fill a critical gap in event-based computer vision research by supplying a high-quality, real-world labeled dataset. Intended to facilitate the development of advanced algorithms for object detection and tracking applications, MEVDT includes multi-modal traffic scene data with synchronized grayscale images and high-temporal-resolution event streams. Additionally, it provides annotations for object detection and tracking with class labels, pixel-precise bounding box coordinates, and unique object identifiers. The dataset is organized into directories containing sequences of images and event streams, comprehensive ground truth labels, fixed-duration event samples, and data indexing sets for training and testing. and To access and utilize the dataset, researchers need specific software or scripts compatible with the data formats included, such as PNG for grayscale images, CSV for event stream data, AEDAT for the encoded fixed-duration event samples, and TXT for annotations. Recommended tools include standard image processing libraries for PNG files and CSV or text parsers for event data. A specialized Python script for reading AEDAT files is available at: https://github.com/Zelshair/cstr-event-vision/blob/main/scripts/data_processing/read_aedat.py, which streamlines access to the encoded event sample data.
- Keyword:
- Computer Vision, Event-Based Vision, Object Detection, Object Tracking, and Multi-Modal Vision Dataset
- Citation to related publication:
- El Shair, Z. and Rawashdeh, S., 2024. MEVDT: Multi-Modal Event-Based Vehicle Detection and Tracking Dataset. Data In Brief (under review)., El Shair, Z. and Rawashdeh, S.A., 2022. High-temporal-resolution object detection and tracking using images and events. Journal of Imaging, 8(8), p.210., El Shair, Z. and Rawashdeh, S., 2023. High-temporal-resolution event-based vehicle detection and tracking. Optical Engineering, 62(3), pp.031209-031209., and El Shair, Z.A., 2024. Advancing Neuromorphic Event-Based Vision Methods for Robotic Perception Tasks (Doctoral dissertation, University of Michigan-Dearborn).
- Discipline:
- Engineering
-
- Creator:
- Whittaker, Collin B. and Jorns, Benjamin A.
- Description:
- This work characterized variability in the emitter geometry of a porous electrospray array thruster. It consists of raw topographic maps taken from the thruster, segmented versions of those maps that divide the measurement domain into individual sites within the array, and the geometric parameters describing each of those sites inferred by regressing a geometric model of an emitter against the data. It also includes copies of the computer code used to perform this analysis and plot the results, written in a combination of Python and MATLAB.
- Discipline:
- Engineering
-
- Creator:
- Fu, Xun, Zhang, Bohao, Weber, Ceri J., Cooper, Kimberly L., Vasudevan, Ram, and Moore, Talia Y.
- Description:
- Tails used as inertial appendages induce body rotations of animals and robots---a phenomenon that is governed largely by the ratio of the body and tail moments of inertia. However, vertebrate tails have more degrees of freedom (e.g., number of joints, rotational axes) than most current theoretical models and robotic tails. To understand how morphology affects inertial appendage function, we developed an optimization-based approach that finds the maximally effective tail trajectory and measures error from a target trajectory. For tails of equal total length and mass, increasing the number of equal-length joints increased the complexity of maximally effective tail motions. When we optimized the relative lengths of tail bones while keeping the total tail length, mass, and number of joints the same, this optimization-based approach found that the lengths match the pattern found in the tail bones of mammals specialized for inertial maneuvering. In both experiments, adding joints enhanced the performance of the inertial appendage, but with diminishing returns, largely due to the total control effort constraint. This optimization-based simulation can compare the maximum performance of diverse inertial appendages that dynamically vary in moment of inertia in 3D space, predict inertial capabilities from skeletal data, and inform the design of robotic inertial appendages.
- Keyword:
- simulation, inertial maneuvering, caudal vertebrae, trajectory optimization, and reconfigurable appendages
- Citation to related publication:
- Xun Fu, Bohao Zhang, Ceri J. Weber, Kimberly L. Cooper, Ram Vasudevan, Talia Y. Moore. (in review) Jointed tails enhance control of three-dimensional body rotation.
- Discipline:
- Engineering and Science
-
- Creator:
- Shah, Bhavarth
- Description:
- The three approaches used three distinct datasets named as follows: Historicalwater_levels.csv, Historical_Precipitation.csv, and Bayesian Statistical dataset.csv. These files are accessible using Microsoft Office or similar software. The machine learning models are developed in Jupyter Notebook (.ipynb) files, named according to the datasets they utilize. However, for the third approach, the models are named Random Forest, LSTM Model Base, and Multivariate LSTM Models. More details are available on the Shah_Bhavarth_Readme.txt. These notebooks can be accessed through Python, Project Jupyter, or Google Colab, and dependencies include libraries such as Pandas, NumPy, Matplotlib, Scikit-learn, Keras, and TensorFlow. The supplementary material also includes Excel files for stage-curve calculations and diversions, named Water_levels_Stage_Curve_Calculations1970-2018.xlsx and Diversions_calculation.xlsx, respectively.
- Keyword:
- Machine learning, Forecasting, Water levels, Mono lake, and Hydrology
- Citation to related publication:
- Shah, Bhavarth. 2024. "Mono Lake Water Levels Forecasting Using Machine Learning." Master’s thesis, University of Michigan, School for Environment and Sustainability. ORCID iD: 0000-0002-2391-8610. https://dx.doi.org/10.7302/22659
- Discipline:
- Science and Engineering
-
- Creator:
- Ali, Hashim, Subramani, Surya , Sudhir, Shefali , Varahamurthy, Raksha , and Malik, Hafiz
- Description:
- Voice-cloning (VC) systems have seen an exceptional increase in the realism of synthesized speech in recent years. The high quality of synthesized speech and the availability of low-cost VC services have given rise to many potential abuses of this technology such as online smearing campaigns and dissemination of fabricated information etc. A number of detection methodologies have been proposed over the years that can detect voice spoofs with reasonably good accuracy. However, these methodologies are mostly evaluated on clean audio databases, such as Asvspoof 2019. This research aims to evaluate state-of-the-art (SOTA) Audio Spoof Detection approaches in the presence of laundering attacks. In that regard, a new laundering attack database, called ASVspoof Laundering Database, is created. This database is based on the ASVspoof 2019 LA eval database comprising a total of 1388.22 hours of audio recordings. Seven SOTA audio spoof detection approaches are evaluated on this laundered database. The results indicate that SOTA systems perform poorly in the presence of aggressive laundering attacks, especially reverberation and additive noise attacks. This suggests the need for robust audio spoof detection.
- Keyword:
- Audio Forensics, Audio Antispoofing, Audio Deepfakes, ASVSpoof, and Machine Learning
- Discipline:
- Engineering
-
- Creator:
- Hong, Yi, Fry, Lauren M., Orendorf, Sophie, Ward, Jamie L., Mroczka, Bryan, Wright, David, and Gronewold, Andrew
- Description:
- Accurate estimation of hydro-meteorological variables is essential for adaptive water management in the North American Laurentian Great Lakes. However, only a limited number of monthly datasets are available nowadays that encompass all components of net basin supply (NBS), such as over-lake precipitation (P), evaporation (E), and total runoff (R). To address this gap, we developed a daily hydro-meteorological dataset covering an extended period from 1979 to 2022 for each of the Great Lakes. The daily P and E were derived from six global gridded reanalysis climate datasets (GGRCD) that include both P and E estimates, and R was calculated from National Water Model (NWM) simulations. Ensemble mean values of the difference between P and E (P – E) and NBS were obtained by analyzing daily P, E, and R. Monthly averaged values derived from our new daily dataset were validated against existing monthly datasets. This daily hydro-meteorological dataset has the potential to serve as a validation resource for current data and analysis of individual NBS components. Additionally, it could offer a comprehensive depiction of weather and hydrological processes in the Great Lakes region, including the ability to record extreme events, facilitate enhanced seasonal analysis, and support hydrologic model development and calibration. The source code and data representation/analysis figures are also made available in the data repository.
- Keyword:
- Great Lakes, Hydrometeorological, National Water Model, Daily, Overlake precipitation, Overlake evaporation, Total runoff, Net Basin Supply, and Water Balance
- Discipline:
- Science and Engineering
-
- Creator:
- Agnit Mukhopadhyay, Sanja Panovska, Raven Garvey, Michael Liemohn, Natalia Ganjushkina, Austin Brenner, Ilya Usoskin, Michael Balikhin, and Daniel Welling
- Description:
- In the recent geological past, Earth’s magnetic field reduced to 4% of the modern values and the magnetic poles moved severely apart from the geographic poles causing the Laschamps geomagnetic excursion, which happened about 41 millennia ago. The excursion lasted for about two millennia, with the peak strength reduction and dipole tilting lasting for a shorter period of 300 years. During this period, the geomagnetic field exhibited significant differences from the modern nearly-aligned dipolar field, causing non-dipole variables to mimic a magnetic field akin to the outer planets while displaying a significantly reduced magnetic strength. However, the precise magnetospheric configuration and their electrodynamic coupling with the atmosphere have remained critically understudied. This dataset contains the first space plasma investigation of the exact geomagnetic conditions in the near-Earth space environment during the excursion. The study contains a full 3D reconstruction and analysis of the geospace system including the intrinsic geomagnetic field, magnetospheric system and the upper atmosphere, linked in sequence using feedback channels for distinct temporal epochs. The reconstruction was conducted using the LSMOD.2 model, Block Adaptive Tree Solar wind-Roe-Upwind Scheme (BATS-R-US) Model and the MAGnetosphere-Ionosphere-Thermosphere (MAGNIT) Auroral Precipitation Model, all of which are publicly-available models. The dataset contains the raw data from each of these models, in addition to the images/post-processing results generated using these models. Paleomagnetic data produced by LSMOD.2 can be visualized using a combination of linear plotting and contour plotting tools available commonly in visualization software like Python (e.g. Python/Matplotlib) or MATLAB. Standard tools to read and visualize BATS-R-US and MAGNIT output are already publicly available using IDL and Python (see SpacePy/PyBats - https://spacepy.github.io/pybats.html). For information and details about the post-processed data, visualization and analysis, please contact the authors for details. The anthropological dataset can be visualized using a shape file reader (e.g. Python/GeoPandas) and a linear plotting tool (e.g. Python/Matplotlib).
- Discipline:
- Engineering and Science
-
- Creator:
- Lee, Shih Kuang, Tsai, Sun Ting, and Glotzer, Sharon C.
- Description:
- The trajectory data and codes were generated for our work "Classification of complex local environments in systems of particle shapes through shape-symmetry encoded data augmentation" (amidst peer review process). The data sets contain trajectory data in GSD file format for 7 test systems, including cubic structures, two-dimensional and three-dimensional patchy particle shape systems, hexagonal bipyramids with two aspect ratios, and truncated shapes with two degrees of truncation. Besides, the corresponding Python code and Jupyter notebook used to perform data augmentation, MLP classifier training, and MLP classifier testing are included.
- Keyword:
- Machine Learning, Colloids Self-Assembly, Crystallization, and Order Parameter
- Citation to related publication:
- https://doi.org/10.48550/arXiv.2312.11822
- Discipline:
- Other, Science, and Engineering
-
- Creator:
- Sheppard, Anja, Sethuraman, Advaith V, Bagoren, Onur, Pinnow, Christopher, Anderson, Jamey, Havens, Timothy C, and Skinner, Katherine A
- Description:
- The AI4Shipwrecks dataset contains sidescan sonar images of shipwrecks and corresponding binary labels collected during 2022 and 2023 at the NOAA Thunder Bay National Marine Sanctuary in Alpena, MI. The data collection platform was an Iver3 Autonomous Underwater Vehicle (AUV) equipped with an EdgeTech 2205 dual-frequency ultra-high resolution sidescan sonar and 3D bathymetric system. The labels were compiled from reference labels created by experts in marine archaeology. The intended use of this dataset is to encourage development of semantic segmentation, object detection, or anomaly detection algorithms in the computer vision field. Comparisons of state-of-the-art segmentation networks on our dataset are shown in the paper. , The file structure is organized as described in the README.txt file, where images in 'images' directories are the waterfall product of sidescan sonar surveys, and images in 'labels' directories are binary representations of expert labels. Images across the 'images' and 'labels' directories are correlated by having identical filenames. In the label images, a pixel value of '0' represents the non-shipwreck/other class and '1' represents the shipwreck class for the correspondingly named image (<wreck_name>_<##>.png) in the images directory. , and The project webpage can be found at: https://umfieldrobotics.github.io/ai4shipwrecks/
- Keyword:
- machine learning, computer vision, field robotics, marine robotics, underwater robotics, sidescan sonar, semantic segmentation, and object detection
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , and Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://umautobots.github.io/nsavp, https://github.com/umautobots/nsavp_tools, and https://sites.google.com/umich.edu/novelsensors2023
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception., The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , and Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://umautobots.github.io/nsavp, https://github.com/umautobots/nsavp_tools, and https://sites.google.com/umich.edu/novelsensors2023
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception., The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , and Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://umautobots.github.io/nsavp, https://github.com/umautobots/nsavp_tools, and https://sites.google.com/umich.edu/novelsensors2023
- Discipline:
- Engineering
-
- Creator:
- Hawes, Jason K, Goldstein, Benjamin P. , Newell, Joshua P. , Dorr, Erica , Caputo, Silvio , Fox-Kämper, Runrid , Grard, Baptiste , Ilieva, Rositsa T. , Fargue-Lelièvre, Agnès , Poniży, Lidia , Schoen, Victoria , Specht, Kathrin , and Cohen, Nevin
- Description:
- Urban agriculture (UA) is a widely proposed strategy to make cities and urban food systems more sustainable. However, its carbon footprint remains understudied. In fact, the few existing studies suggest that UA may be worse for the climate than conventional agriculture. This is the first large-scale study to resolve this uncertainty across cities and types of UA, employing citizen science at 73 UA sites in Europe and the United States to compare UA products to food from conventional farms. The results reveal that food from UA is six times as carbon intensive as conventional agriculture (420g vs 70g CO2 equivalent per serving). Some UA crops (e.g., tomatoes) and sites (e.g., 25% of individually-managed gardens), however, outperform conventional agriculture. These exceptions suggest that UA practitioners can reduce their climate impacts by cultivating crops that are typically greenhouse grown or air-freighted, maintaining UA sites for many years, and leveraging waste as inputs.This database contains the necessary reference material to trace the path of our analysis from raw garden data to carbon footprint and nutrient results. It also contains the final results of the analyses in various extended forms not available in the publication. For more information, see manuscript at link below. (Introduction partially quoted from Hawes et al., 2023)
- Citation to related publication:
- Hawes, J. K., Goldstein, B. P., Newell, J. P., Dorr, E., Caputo, S., Fox-Kämper, R., Grard, B., Ilieva, R. T., Fargue-Lelièvre, A., Poniży, L., Schoen, V., Specht, K., & Cohen, N. (2024). Comparing the carbon footprints of urban and conventional agriculture. Nature Cities, 1–10. https://doi.org/10.1038/s44284-023-00023-3
- Discipline:
- Engineering
-
- Creator:
- Lee, Sophie Y., Schönhöfer Philipp W.A., and Glotzer, Sharon C.
- Description:
- This dataset was generated for our work: "Complex motion of steerable vesicular robots filled with active colloidal rods". In this project, we used Brownian molecular dynamics simulations to study the rich dynamical behavior of rigid kinked vesicles that contain self-propelling rod-shaped particles. We identified that kinks in the vesicle membrane bias the emergent clustering and alignment of the active agents. Based on the system's geometrical and material properties, we were able to design multiple types of directed motion of the vesicle superstructure. This dataset includes simulation data for two-dimensional systems of self-propelling rod particles confined by teardrop-shaped coarse-grained vesicles. The trajectory of each simulation is saved in a GSD format file with parameter metadata in a JSON file. Due to the large number of replicas of each pair of parameters, simulation data were grouped into 5 different folders. Collective quantitative analysis for simulated trajectories was performed with Jupyter Notebook. and Workspaces_simulations.zip contains all the workspaces of simulations Each folder has subfolders called 'dimer' and 'trimer' depending on the length of the propelling rod particles used in the simulation. (Except for the folder 'number-density_16' which has only 'dimer') In the subfolders, we include the Python scripts used in this work for simulating and trajectory analysis for individual trajectory data. The parameter space of each folder is noted in init.py. Analysis_jupyter_notebooks.zip includes Jupyter notebooks that can reproduce the collective analysis done for this work.
- Discipline:
- Engineering
-
- Creator:
- Gill, Tate M, Sercel, Christopher L, and Jorns, Benjamin A
- Description:
- Rotating Magnetic Field (RMF) thrusters are a form of electrodeless plasma propulsion. This technology is a low maturity but potentially enabling candidate for high-power in-space propulsion for use with alternative propellants. The purpose of the data here, and the associated publication is to evaluate the phenomenological efficiency modes for this thruster test article to explain and understand its overall efficiency. These modes include divergence, power coupling, mass utilization, and plasma/acceleration efficiency. Additional time-resolved measurements of the internal plasma properties were performed using a triple Langmuir probe to evaluate energy loss processes within the thruster.
- Keyword:
- Electric Propulsion, Rotating Magnetic Field Thrusters, Inductive Pulsed Plasma Thrusters, and Magnetic Nozzles
- Citation to related publication:
- Gill, T.M., Sercel, C.L., and Jorns, B.A., "Experimental Investigation into Efficiency Loss in Rotating Magnetic Field Thrusters", Plasma Sci. Sources and Tech. 2023 (In Review)
- Discipline:
- Engineering
-
- Creator:
- Lin, Brian T. W.
- Description:
- This footage is an output of a USDOT-funded project titled "Development of Machine-Learning Models for Autonomous Vehicle Decisions on Weaving Sections of Freeway Ramps." It showcases an automated weaving maneuver within an augmented reality environment. During the demonstration, Mcity's automated vehicle navigates through a highway weaving section, making a lane change while interacting with a virtual vehicle. In this instance, Mcity's vehicle was operated by automated driving systems, which executed the lane change based on the detection for external environmental factors and parameter inputs received from the virtual vehicle.
- Discipline:
- Engineering
-
- Creator:
- Chaoran Xu, Davlasheridze, Meri, Nelson-Mercer, Benjamin T., Bricker, Jeremy D., Jia, Jianjun, and Ross, Ashley D.
- Description:
- Hurricane Ike, which struck the United States in September 2008, was the ninth most expensive hurricane in terms of damages. It caused nearly $30 billion in damage, of which nearly $12B were insured losses, after making landfall on the Bolivar Peninsula, Texas. We used the Delft3d-FM/SWAN hydrodynamic and spectral wave model to simulate the storm surge inundation around Galveston Bay during Hurricane Ike. Damage curves were established through the eight hydrodynamic parameters (water depth, flow velocity, unit discharge, flow momentum flux, significant wave height, wave energy flux, total water depth (flow depth plus wave height), and total (flow plus wave) force) simulated by the model. We found that the damage curves are sensitive to the model grid resolution, building elevation, and the number of stories.
- Citation to related publication:
- Xu et al. (2023). Damage curves derived from Hurricane Ike in the west of Galveston Bay based on insurance claims and hydrodynamic simulations.
- Discipline:
- Engineering
-
- Creator:
- Brenner, Austin M
- Description:
- Results of computer simulation of near Earth space is looked at in a new way to understand how energy moves around the global system. It is found that in addition to a pathway of energy from the outside into the system and back again there is an internal loop which recirculates energy. These new methods will greatly improve our understanding how the whole magnetosphere system evolves and will help address evolution of processes that have space weather impacts.
- Keyword:
- Energy flux, geospace, magnetopause, magnetosphere, poynting flux, and reconnection
- Citation to related publication:
- Austin Brenner, Tuija I. Pulkkinen, Qusai Al Shidi, et al. Dissecting Earth’s Magnetosphere: 3D Energy Transport in a Simulation of a Real Storm Event. ESS Open Archive . August 04, 2023.
- Discipline:
- Science and Engineering
-
- Creator:
- Hung, Adam, Enninful Adu, Challen, and Moore, Talia Y.
- Description:
- The CAD files can be opened by any CAD software. The code is in Arduino and Python. The URDF was generated using Solidworks.
- Keyword:
- robotics, omnidirectional, tripod, ballbot, gliding, and rolling
- Citation to related publication:
- Hung, A., Enninful Adu, C., Moore, T.Y. (in review), SKOOTR: A SKating, Omni-Oriented, Tripedal Robot for dynamically stable indoor navigation. IEEE ICRA
- Discipline:
- Engineering
-
- Creator:
- Wallace, Dylan M, Benyamini, Miri, Nason-Tomaszewski, Samuel R, Costello, Joseph T, Cubillos, Luis H, Mender, Matthew J, Temmar, Hisham, Willsey, Matthew S, Patil, Parag P, Chestek, Cynthia A, and Zacksenhouse, Miriam
- Description:
- This is data from Wallace, Benyamini et al., 2023, Journal of Neural Engineering. There are two sets of data included: 1. Neural features and error labels used to train error classifiers for each day used in the study 2. Trial data from an example experiment day (Monkey N, Day 6), with runs for offline calibration, online brain control, error monitoring, and error correction. The purpose of this study was to investigate the use of error signals in motor cortex to improve brain-machine interface (BMI) performance for control of two finger groups. All data is contained in .mat files, which can be opened using MATLAB or the Python SciPy library.
- Keyword:
- Brain-machine interface (BMI), Error detection, and Neural recording
- Citation to related publication:
- Wallace, D. M., Benyamini, M., Nason-Tomaszewski, S. R., Costello, J. T., Cubillos, L. H., Mender, M. J., Temmar, H., Willsey, M. S., Patil, P. G., Chestek, C. A., & Zacksenhouse, M. (2023). Error detection and correction in intracortical brain–machine interfaces controlling two finger groups. Journal of Neural Engineering, 20(4), 046037. https://doi.org/10.1088/1741-2552/acef95
- Discipline:
- Engineering, Science, and Health Sciences
-
- Creator:
- Dwyer, Tobias, Moore, Timothy C., Anderson, Joshua A. , and Glotzer, Sharon C.
- Description:
- This dataset was generated for our work: "Tunable Assembly of Host–Guest Colloidal Crystals". The data set contains data for 5 different binary systems of star particles and convex guests, and one system of only star particles. All simulation were formed at constant pressure. The data set contains GSD files for each of the simulations used in this work along with the corresponding python code used to produce the simulations. We also include the python code and jupyter notebook to produce the free volume calculations used in this work. and How to use this Data: Simulation Data: We include GSD files that can be uploaded into a visualization or analysis software such as Ovito or Freud for independent analysis. Simulation python scripts (workspaces_for_HPMC_simulations.zip): We include the python scripts used in this work for simulating host guest systems at constant pressure. Free Volume Data (Free_volume_calculations_and_analysis.zip): You can run the jupyter notebook included here to reproduce the free volume analysis for this work. We also include the python scripts for the free volume calculation python scripts that get the data for these free volume calculations.
- Citation to related publication:
- Dwyer, T, Moore, TC, Anderson, JA, & Glotzer, SC. Tunable Assembly of Host–Guest Colloidal Crystals. Soft Matter (Provisional Citation)
- Discipline:
- Engineering
-
- 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
-
- Creator:
- Elvati, Paolo, Luyet, Chloe, Wang, Yichun, Liu, Changjiang, VanEpps, J. Scott, Kotov, Nicholas A., and Violi, Angela
- Description:
- Amyloid nanofibers are abundant in microorganisms and are integral components of many biofilms, serving various purposes, from virulent to structural. Nonetheless, the precise characterization of bacterial amyloid nanofibers has been elusive, with incomplete and contradicting results. The present work focuses on the molecular details and characteristics of PSMa1-derived functional amyloids present in Staphylococcus aureus biofilms, using a combination of computational and experimental techniques, to develop a model that can aid the design of compounds to control amyloid formation. Results from molecular dynamics simulations, guided and supported by spectroscopy and microscopy, show that PSMa1 amyloid nanofibers present a helical structure formed by two protofilaments, have an average diameter of about 12 nm, and adopt a left-handed helicity with a periodicity of approximately 72 nm. The chirality of the self-assembled nanofibers, an intrinsic geometric property of its constituent peptides, is central to determining the fibers' lateral growth.
- Keyword:
- molecular self-assembly, computational nanotechnology, nanobiotechnology, and structural properties
- Citation to related publication:
- Paolo Elvati, Chloe Luyet, Yichun Wang, Changjiang Liu, J. Scott VanEpps, Nicholas A. Kotov, and Angela Violi ACS Applied Nano Materials 2023 6 (8), 6594-6604 DOI: 10.1021/acsanm.3c00174
- Discipline:
- Engineering and Science
-
- Creator:
- Luyet, Chloe, Elvati, Paolo, Vinh, Jordan, and Violi, Angela
- Description:
- A growing body of work has linked key biological activities to the mechanical properties of cellular membranes, and as a means of identification. Here, we present a computational approach to simulate and compare the vibrational spectra in the low-THz region for mammalian and bacterial membranes, investigating the effect of membrane asymmetry and composition, as well as the conserved frequencies of a specific cell. We find that asymmetry does not impact the vibrational spectra, and the impact of sterols depends on the mobility of the components of the membrane. We demonstrate that vibrational spectra can be used to distinguish between membranes and, therefore, could be used in identification of different organisms. The method presented, here, can be immediately extended to other biological structures (e.g., amyloid fibers, polysaccharides, and protein-ligand structures) in order to fingerprint and understand vibrations of numerous biologically-relevant nanoscale structures.
- Keyword:
- molecular dynamics, membranes, mechanical vibration, bacterial identification, and Staphylococcus aureus
- Citation to related publication:
- Luyet C, Elvati P, Vinh J, Violi A. Low-THz Vibrations of Biological Membranes. Membranes. 2023; 13(2):139. https://doi.org/10.3390/membranes13020139
- Discipline:
- Engineering
-
- Creator:
- Klinich, Kathleen D, Hu, Jingwen, Boyle, Kyle J, Manary, Miriam A., and Orton, Nichole R
- Description:
- As part of a project to develop side impact test procedures for evaluating wheelchairs, wheelchair tiedowns and occupant restraint systems (WTORS), and vehicle-based occupant protection systems for wheelchair seating stations, we created validated finite element (FE) models to support procedure development. Models were constructed using LS-DYNA. Dynamic sled tests were performed to validate the FE models of surrogate fixtures and commercial hardware. Validated FE models were developed for the Surrogate wheelchair base (SWCB), Surrogate wheelchair for side impact (SWCSI), a manual wheelchair (Ki Mobility Catalyst 5), and a power wheelchair (Quantum Rehab Edge 2.0). Additional FE models of a heavy-duty anchor meeting the Universal Docking Interface Geometry (UDIG), surrogate four-point strap tiedowns (SWTORS), a traditional docking station, and the surrogate wall fixture were also developed.
- Keyword:
- finite element, wheelchair, transportation, and tiedown
- Discipline:
- Engineering
-
- Creator:
- Klinich, Kathleen D, Lin, Brian, and Moore, Jamie L.
- Description:
- This dataset allows comparison of the different strategies implemented by vehicle manufacturers being used to communicate with drivers. Spreadsheets were created in MS Excel to summarize data for each vehicle, and include page numbers in each vehicle owner's manual for reference. The photos taken of each vehicle control panel allow detailed inspection of the displays and controls.
- Keyword:
- vehicle, controls, displays, and FMVSS 101
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal imaging, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Yining Shi
- Description:
- Statistical study of residuals between Swarm observations and IGRF-13 geomagnetic field model larger than 300 nT in northern and southern hemisphere. Data analysis done on https://viresclient.readthedocs.io/en/latest/ These data are generated to conduct a statistical study of the locations of large residuals in the two hemispheres for a better understanding of potential error in satellite aviation application when using Earth magnetic field models like IGRF as references, as well as the energy transfer in the magnetosphere-ionosphere-thermosphere coupling. Interhemispheric asymmetries are found in the locations of the large residuals due to the difference in geographic pole locations.
- Discipline:
- Engineering
-
- Creator:
- Rivera-Rivera, Luis Y., Moore, Timothy C., and Glotzer, Sharon C.
- Description:
- The dataset is organized as follows: the data for each of the three target structures is contained within a directory with the structure name (e.g., kagome, pyrocholore and snub-square). Within each structure directory, data obtained from alchemical and self-assembly simulations are separated into alchem and self-assembly directories respectively. An additional suboptimal-self-assembly directory is only present for the snub-square structure and contains the data for the pattern registration analysis discussed in the SI. For a detailed description of each file contained within each directory, please refer to the README file.
- Keyword:
- inverse design, self-assembly, triblock Janus particles, crystallization slot, and digital alchemy
- Citation to related publication:
- Rivera-Rivera, LY, Moore, TC & SC Glotzer. Inverse design of triblock Janus spheres for self-assembly of complex structures in the crystallization slot via digital alchemy. Soft Matter, 2023, 19, 2726-2736 doi: 10.1039/d2sm01593e
- Discipline:
- Engineering
-
- Creator:
- Thompson, Ellen P. and Ellis, Brian R.
- Description:
- Accurate prediction of physical alterations in carbonate reservoirs under dissolution is critical for development of subsurface energy technologies. The impact of mineral dissolution on flow characteristics depends on the connectivity and tortuosity of the pore network. Persistent homology is a tool from algebraic topology that describes the size and connectivity of topological features. When applied to 3D X-ray computed tomography (XCT) imagery of rock cores, it provides a novel metric of pore network heterogeneity. Prior works have demonstrated the efficacy of persistent homology in predicting flow properties in numerical simulations of flow through porous media. Its ability to combine size, spatial distribution, and connectivity information make it a promising tool for understanding reactive transport in complex pore networks, yet limited work has been done to apply persistence analysis to experimental studies on natural rocks. In this study, three limestone cores were imaged by XCT before and after acid-driven dissolution flow through experiments. Each XCT scan was analyzed using persistent homology. In all three rocks, permeability increase was driven by the growth of large, connected pore bodies. The two most homogenous samples saw an increased effect nearer to the flow inlet, suggesting emerging preferential flow paths as the reaction front progresses. The most heterogeneous sample showed an increase in along-core homogeneity during reaction. Variability of persistence showed moderate positive correlation with pore body size increase. Persistence heterogeneity analysis could be used to anticipate where greatest pore size evolution may occur in a reservoir targeted for subsurface development, improving confidence in project viability.
- Keyword:
- Carbonate dissolution, X-ray computed tomography, Porous media, Topology, and Persistent homology
- Citation to related publication:
- Thompson, E.P.; Ellis, B.R. (2023) Persistent Homology as a Heterogeneity Metric for Predicting Pore Size Change in Dissolving Carbonates. In Review.
- Discipline:
- Science and Engineering
-
- Creator:
- Skinner, Katherine A. , Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection released in support of an IROS 2023 workshop publication, with a supporting website ( https://sites.google.com/umich.edu/novelsensors2023). To enable new research in the area of novel sensors for autonomous vehicles, these datasets are designed for the task of place recognition with novel sensors. To our knowledge, this new dataset is the first to include stereo thermal cameras together with stereo event cameras and stereo monochrome cameras, which perform better in low-light than RGB cameras., The dataset collection platform is a Ford Fusion vehicle with roof-mounted sensing suite, which consists of forward-facing stereo uncooled thermal cameras (FLIR Boson 640+ ADK), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) aligned with ground truth position from a high precision navigation system. Sequences include ~10 km routes, which may be driven repeatedly under varying lighting conditions and feature instances of direct sunlight and low-light that challenge conventional cameras., and A software toolkit to facilitate efficient use of the dataset including dataset download, application of calibration parameters, and evaluation of place recognition results based on standard metrics (e.g., maximum recall at 100% precision). These software tools for converting, managing, and viewing datafiles can be found at the associated GitHub repository ( https://github.com/umautobots/nsavp_tools).
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023 and https://github.com/umautobots/nsavp_tools
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A. , Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection released in support of an IROS 2023 workshop publication, with a supporting website ( https://sites.google.com/umich.edu/novelsensors2023). To enable new research in the area of novel sensors for autonomous vehicles, these datasets are designed for the task of place recognition with novel sensors. To our knowledge, this new dataset is the first to include stereo thermal cameras together with stereo event cameras and stereo monochrome cameras, which perform better in low-light than RGB cameras., The dataset collection platform is a Ford Fusion vehicle with roof-mounted sensing suite, which consists of forward-facing stereo uncooled thermal cameras (FLIR Boson 640+ ADK), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) aligned with ground truth position from a high precision navigation system. Sequences include ~10 km routes, which may be driven repeatedly under varying lighting conditions and feature instances of direct sunlight and low-light that challenge conventional cameras., and A software toolkit to facilitate efficient use of the dataset including dataset download, application of calibration parameters, and evaluation of place recognition results based on standard metrics (e.g., maximum recall at 100% precision). These software tools for converting, managing, and viewing datafiles can be found at the associated GitHub repository ( https://github.com/umautobots/nsavp_tools).
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023 and https://github.com/umautobots/nsavp_tools
- Discipline:
- Engineering
-
- Creator:
- Wu, Ziyou and Revzen, Shai
- Description:
- The data in this repository is a nearly unique dataset at the time of its making -- precise measurements of all contact forces of a 6-legged robot during multi-legged slipping motions and regular walking. These data were collected to establish the validity of the observation presented in this article: Zhao et al. Walking is like slithering: A unifying, data-driven view of locomotion. (2022) PNAS 119(37): e113222119. DOI: https://doi.org/10.1073/pnas.2113222119
- Keyword:
- robot, locomotion, and multilegged
- Citation to related publication:
- Science Robotics paper being submitted
- Discipline:
- Engineering
-
- Creator:
- Tandon, Suyash, Johnsen, Eric, and Maki, Kevin
- Description:
- Passive flow control devices, such as vortex generators (VGs), can effectively modulate the turbulent boundary layer flow near regions of adverse pressure gradients, but the interactions between the salient flow structures produced by VGs and those of the separated flow are not fully understood. In this study, a spatially evolving turbulent boundary layer interacting with a wall-mounted cube ahead of a backward-facing ramp is investigated using wall-resolved large-eddy simulations for a Reynolds number of 19,600, based on the inlet boundary layer thickness and freestream velocity. Different cube configurations are examined to isolate the effects of cube height and streamwise position.
- Keyword:
- fluid mechanics, boundary layer , turbulence, separated flows, and large eddy simulation
- Citation to related publication:
- Suyash Tandon, Kevin J. Maki, and Eric Johnsen, "Large-Eddy Simulations of Flow over a Backward-Facing Ramp with a Wall-Mounted Cube, " AIAAJ, Vol. 62, No. 9 (2024), pp. 3403-3417 doi: doi/abs/10.2514/1.J063803
- Discipline:
- Engineering and Science
-
- Creator:
- Gill, Tate M.
- Description:
- Data included in raw format in addition to the MATLAB scripts used for processing into final results. If there are issues or confusion regarding this data or the codes, feel free to contact me at tategill@umich.edu.
- Keyword:
- Electric Propulsion
- Discipline:
- Engineering
-
- Creator:
- Hepner, Shadrach, T
- Description:
- This data provided evidence of the presence of a lower hybrid drift instability in a magnetic nozzle. It was used in DOI: 10.1063/5.0012668 to estimate the effective electron collision frequency that it induced in the context of cross-field electron transport. It is also used to determine the effective reduction in heat flux resulting from propagation along magnetic field lines in an upcoming work.
- Keyword:
- Magnetic nozzle, heat flux, plasma instabilities
- Citation to related publication:
- Hepner, S., Jorns, B. (2020). Wave-driven non-classical electron transport in a low temperature magnetically expanding plasma. Appl. Phys. Lett, 116(263502). https://doi.org/10.1063/5.0012668
- Discipline:
- Engineering
-
- Creator:
- Jones, Kaylin and Cotel, Aline J
- Description:
- To enhance environmental turbulence measurements, we have designed and constructed a novel Particle Image Velocimetry (PIV) instrument intended for field use. The data contained here was used for either validation of the instrument, or was produced by the instrument in proof-of-concept field testing.
- Keyword:
- particle image velocimetry, environmental turbulence, and field instrumentation
- Citation to related publication:
- Jones, K., and Cotel, A.J. 2023. Low-cost field particle image velocimetry for quantifying environmental turbulence. Journal of Ecohydraulics.
- Discipline:
- Engineering
-
- Creator:
- Lin, Austin J, Lei, Shunbo, Keskar, Aditya, Hiskens, Ian A, Johnson, Jeremiah X , Mathieu, Johanna L, Kennedy, Tim, DeMink, Scott, Morgan, Kevin, Flynn, Connor, Giessner, Paul, Anderson, David, Dongmo, Jordan, Afshari, Sina, Li, Han, and Ceilsinki, Andrew
- Description:
- This is a subset of the SHIFDR dataset collection containing data from 14 buildings in Southeast Michigan. The full dataset collection can be found at https://deepblue.lib.umich.edu/data/collections/vh53ww273?locale=en and Organization: We include a subfolder for each building, identified by name. All buildings have been renamed after lakes to protect the identity of the building. Within each building subfolder, there is fan power (i.e. current measurements from which fan power can be computed), building automation system (BAS), whole building electrical load (WBEL), and voltage data collected over the course of our experimentation from 2017 to 2021. All experiments were conducted in the summer months and a full schedule of Demand Response (DR) events is included along with each building in the ‘Event_Schedule.csv’ file. The building information file contains general information about the buildings, pertinent to the experiments we conducted. There is also a folder labeled ‘2021 Preprocessed data’ which contains combined BAS and fan power data from the summer of 2021. This data has been lightly processed to calculate fan power from current measurements and interpolate BAS data to 1 minute intervals. These act as an easy-to-use starting point for data analysis.
- Citation to related publication:
- A.J. Lin, S. Lei, A. Keskar, I.A. Hiskens, J.X. Johnson, and J.L. Mathieu. “The Sub-metered HVAC Implemented For Demand Response (SHIFDR) Dataset,” Submitted, 2023.
- Discipline:
- Engineering
-
- Creator:
- Hoffmann, Alex P.
- Description:
- Research Overview: In situ magnetic field measurements are often difficult to obtain due to the presence of stray magnetic fields generated by spacecraft electrical subsystems. The conventional solution is to implement strict magnetic cleanliness requirements and place magnetometers on a deployable boom. However, this method is not always feasible on low-cost platforms due to factors such as increased design complexity, increased cost, and volume limitations. To overcome this problem, we propose using the Quad-Mag CubeSat magnetometer with an improved Underdetermined Blind Source Separation (UBSS) noise removal algorithm. The Quad-Mag consists of four magnetometer sensors in a single CubeSat form-factor card that allows distributed measurements of stray magnetic fields. The UBSS algorithm can remove stray magnetic fields without prior knowledge of the magnitude, orientation, or number of noise sources. UBSS is a two-stage algorithm that identifies signals through cluster analysis and separates them through compressive sensing. We use UBSS with single source point (SSP) detection to improve the identification of noise signals and iteratively-weighted compressed sensing to separate noise signals from the ambient magnetic field. Using a mock CubeSat, we demonstrate in the lab that UBSS reduces four noise signals producing more than 100 nT of noise at each magnetometer to below the expected instrument resolution (near 5 nT). Additionally, we show that the integrated Quad-Mag and improved UBSS system works well for 1U, 2U, 3U, and 6U CubeSats in simulation. Our results show that the Quad-Mag and UBSS noise cancellation package enables high-fidelity magnetic field measurements from a CubeSat without a boom.
- Keyword:
- source separation, demixing, magnetometers, stray magnetic fields, noise removal, and cubesat
- Citation to related publication:
- Hoffmann, A. P., Moldwin, M. B., Strabel, B. P., & Ojeda, L. V. (2023). Enabling Boomless CubeSat Magnetic Field Measurements with the Quad-Mag Magnetometer and an Improved Underdetermined Blind Source Separation Algorithm. Journal of Geophysical Research: Space Physics, 128, e2023JA031662. https://doi-org.proxy.lib.umich.edu/10.1029/2023JA031662
- Discipline:
- Engineering
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