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- Creator:
- Vasudevan, Ram, Barto, Charles, Rosaen, Karl, Mehta, Rounak, Matthew, Johnson-Roberson, and Nittur Sridhar, Sharath
- Description:
- A dataset for computer vision training obtained from long running computer simulations
- Keyword:
- autonomous driving, simulation, Computer Vision and Pattern Recognition, deep learning, Computer Science, object detection, and Robotics
- Citation to related publication:
- 2016arXiv161001983J
- Discipline:
- Engineering
- Title:
- FCAV Simulation Dataset
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- Creator:
- Bougher, Stephen W. (CLaSP Department, U. of Michigan) and Roeten, Kali J. (CLaSP Department, U. of Michigan)
- Description:
- The NASA MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft, which is currently in orbit around Mars, has been taking monthly measurements of the speed and direction of the winds in the upper atmosphere of Mars between about 140 to 240 km above the surface. The observed wind speeds and directions change with time and location, and sometimes fluctuate quickly. These measurements are compared to simulations from a computer model of the Mars atmosphere called M-GITM (Mars Global Ionosphere-Thermosphere Model), developed at U. of Michigan. This is the first comparison between direct measurements of the winds in the upper atmosphere of Mars and simulated winds and is important because it can help to inform us what physical processes are acting on the observed winds. Some wind measurements have similar wind speeds or directions to those predicted by the M-GITM model, but sometimes, there are large differences between the simulated and measured winds. The disagreements between wind observations and model simulations suggest that processes other than normal solar forcing may become relatively more important during these observations and alter the expected circulation pattern. Since the global circulation plays a role in the structure, variability, and evolution of the atmosphere, understanding the processes that drive the winds in the upper atmosphere of Mars provides key context for understanding how the atmosphere behaves as a whole system. A basic version of the M-GITM code can be found on Github as follows: https:/github.com/dpawlows/MGITM and About 30 Neutral Gas and Ion Mass Spectrometer (NGIMS) wind campaigns (of 5 to 10 orbits each) have been conducted by the MAVEN team (Benna et al., 2019). Five of these campaigns are selected for detailed study (Roeten et al. 2019). The Mars conditions for these five campaigns have been used to launch corresponding M-GITM code simulations, yielding 3-D neutral wind fields for comparison to these NGIMS wind observations. The M-GITM datacubes used to extract the zonal and meridional neutral winds, along the trajectory of each orbit path between 140 and 240 km, are provided in this Deep Blue Data archive. README files are provided for each datacube, detailing the contents of each file. A general README file is also provided that summarizes the inputs and outputs of the M-GITM code simulations for this study.
- Keyword:
- Mars, MAVEN spacecraft, Mars thermosphere, and Mars global upper atmosphere winds
- Citation to related publication:
- Roeten, K. J., S. W. Bougher, M. Benna, P. R. Mahaffy, Y. Lee, D. Pawlowski, F. Gonzalez-Galindo, M. Lopez-Valverde, MAVEN/NGIMS thermospheric neutral wind observations: Interpretation using the M-GITM general circulation Model, J. Geophysical Research, submitted (2019)
- Discipline:
- Engineering and Science
- Title:
- Mars Thermospheric Neutral Winds: Mars Global Ionosphere-Thermosphere Model (M-GITM) Simulated Datasets for Comparison to MAVEN Spacecraft Measurements
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- Creator:
- Crisp, Dakota N., Saggio, Maria L., Scott, Jared, Stacey, William C., Nakatani, Mitsuyoshi, Gliske, Stephen V., and Lin, Jack
- Description:
- This data and scripts are meant to test and show seizure differentiation based on bifurcation theory. A zip file is included which contains real and simulated seizure waveforms, Matlab scripts, and metadata. The matlab scripts allow for visual review validation and objective feature analysis. The file “README.txt” provides more detail about each individual file within the zip file. and Data citation: Crisp, D.N., Saggio, M.L., Scott, J., Stacey, W.C., Nakatani, M., Gliske, S.F., Lin, J. (2019). Epidynamics: Navigating the map of seizure dynamics - Code & Data [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/ejhy-5h41
- Keyword:
- Bifurcation, Epilepsy, Seizure, and Divergence
- Citation to related publication:
- Discipline:
- Engineering, Science, and Health Sciences
- Title:
- Epidynamics: Navigating the map of seizure dynamics - Code & Data
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- Creator:
- Crisp, Dakota N., Cheung, Warwick, Gliske, Stephen V., Lai, Alan, Freestone, Dean R., Grayden, David B., Cook, Mark J., and Stacey, William C.
- Description:
- The data and the scripts are to show that seizure onset dynamics and evoked responses change over the progression of epileptogenesis defined in this intrahippocampal tetanus toxin rat model. All tests explored in this study can be repeated with the data and scripts included in this repository. and Dataset citation: Crisp, D.N., Cheung, W., Gliske, S.V., Lai, A., Freestone, D.R., Grayden, D.B., Cook, MJ., Stacey, W.C. (2019). Epileptogenesis modulates spontaneous and responsive brain state dynamics [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/r6vg-9658
- Keyword:
- evoked response, stimulation, bifurcation, epilepsy, seizure, divergence, and dynamics
- Citation to related publication:
- Discipline:
- Engineering, Science, and Health Sciences
- Title:
- Epileptogenesis modulates spontaneous and responsive brain state dynamics - Code & Data
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- Creator:
- Ruas, Terry, Ferreira, Charles H. P., Grosky, William, França, Fabrício O., and Medeiros, Débora M. R,
- Description:
- The relationship between words in a sentence often tell us more about the underlying semantic content of a document than its actual words, individually. Recent publications in the natural language processing arena, more specifically using word embeddings, try to incorporate semantic aspects into their word vector representation by considering the context of words and how they are distributed in a document collection. In this work, we propose two novel algorithms, called Flexible Lexical Chain II and Fixed Lexical Chain II that combine the semantic relations derived from lexical chains, prior knowledge from lexical databases, and the robustness of the distributional hypothesis in word embeddings into a single decoupled system. In short, our approach has three main contributions: (i) unsupervised techniques that fully integrate word embeddings and lexical chains; (ii) a more solid semantic representation that considers the latent relation between words in a document; and (iii) lightweight word embeddings models that can be extended to any natural language task. Knowledge-based systems that use natural language text can benefit from our approach to mitigate ambiguous semantic representations provided by traditional statistical approaches. The proposed techniques are tested against seven word embeddings algorithms using five different machine learning classifiers over six scenarios in the document classification task. Our results show that the integration between lexical chains and word embeddings representations sustain state-of-the-art results, even against more complex systems. Github: https://github.com/truas/LexicalChain_Builder
- Keyword:
- document classification, lexical chains, word embeddings, synset embeddings, chain2vec, and natural language processing
- Citation to related publication:
- Discipline:
- Engineering, Science, and Other
- Title:
- Enhanced word embeddings using multi-semantic representation through lexical chains
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- Creator:
- Ledva, Gregory S., Zhe, Du, Peterson, Sarah, Balzano, Laura, and Mathieu, Johanna L.
- Description:
- This is the code that resulted from NSF grant ECCS-1508943, "Inferring the behavior of distributed energy resources from incomplete measurements." The project focused on developing control, estimation, and modeling methods for residential demand response and electric distribution networks. The talks, papers, and poster in Deep Blue: http://hdl.handle.net/2027.42/149480
- Keyword:
- online learning, energy disaggregation, residential demand response, networked control, Kalman filter, and frequency regulation
- Citation to related publication:
- Ledva, Gregory S., Laura Balzano, and Johanna L. Mathieu. "Inferring the behavior of distributed energy resources with online learning." 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2015., Ledva, Gregory S., and Johanna L. Mathieu. "A linear approach to manage input delays while supplying frequency regulation using residential loads." 2017 American Control Conference (ACC). IEEE, 2017., Ledva, Gregory S., Laura Balzano, and Johanna L. Mathieu. "Exploring Connections Between a Multiple Model Kalman Filter and Dynamic Fixed Share with Applications to Demand Response." 2018 IEEE Conference on Control Technology and Applications (CCTA). IEEE, 2018., Ledva, Gregory S., et al. "Disaggregating Load by Type from Distribution System Measurements in Real Time." Energy Markets and Responsive Grids. Springer, New York, NY, 2018. 413-437., Ledva, Gregory S., Sarah Peterson, and Johanna L. Mathieu. "Benchmarking of Aggregate Residential Load Models Used for Demand Response." 2018 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2018., Ledva, Gregory S., et al. "Managing communication delays and model error in demand response for frequency regulation." IEEE Transactions on Power Systems 33.2 (2018): 1299-1308., Ledva, Gregory S., Laura Balzano, and Johanna L. Mathieu. "Real-time energy disaggregation of a distribution feeder's demand using online learning." IEEE Transactions on Power Systems 33.5 (2018): 4730-4740., and Talks, papers, and poster in Deep Blue: http://hdl.handle.net/2027.42/149480
- Discipline:
- Engineering
- Title:
- Inferring the behavior of distributed energy resources from incomplete measurements (project outputs)
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- Creator:
- Yao, Mengqi, Mathieu, Johanna L., Hiskens, Ian A., Molzahn, Daniel K., Koorehdavoudi, Kasra , and Roy, Sandip
- Description:
- The files include all the published paper and presentation source codes. Please install Matpower before running the code. The Matpower version is 5.1, which can be found in https://matpower.org/download/ Talks, papers, and poster in Deep Blue: http://hdl.handle.net/2027.42/150104
- Keyword:
- Demand response, Optimal power flow, Power system voltage stability, and Power system small signal stability L
- Citation to related publication:
- https://ieeexplore.ieee.org/document/8686211, https://ieeexplore.ieee.org/abstract/document/7980798, https://pdfs.semanticscholar.org/a83a/cb9c9af878f8b5d77f4b4230dfb5bd8c5325.pdf, https://ieeexplore.ieee.org/abstract/document/8619091, and https://ieeexplore.ieee.org/abstract/document/8262731
- Discipline:
- Engineering
- Title:
- Demand response algorithms to improve electric power system stability margins
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- Creator:
- Bowen Li, Yiling Zhang, Siqian Shen, and Johanna Mathieu
- Description:
- The project outputs summarize all the publications, talks, and codes we accomplished under this NSF funding. In the project, we develop methodologies to manage uncertainty in future electric power systems and quantify how uncertainty affects power system sustainability. and Talks, papers, and poster in Deep Blue: http://hdl.handle.net/2027.42/149653
- Keyword:
- chance constraint, distributionally robust optimization, optimal power flow, demand response, and unimodality
- Citation to related publication:
- Talks, papers, and poster in Deep Blue: http://hdl.handle.net/2027.42/149653
- Discipline:
- Engineering
- Title:
- Data-driven approaches to managing uncertain load control in sustainable power systems (project outputs)
-
- Creator:
- Bougher, S. W. (CLaSP Department, U. of Michigan), Roeten, K. J. (CLaSP Department, U. of Michigan), and Sharrar, R. (Astronomy Department, U. of Michigan)
- Description:
- The NASA MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft, which is currently in orbit around Mars, has been taking daily (systematic) measurements of the densities and temperatures in the upper atmosphere of Mars between about 140 to 240 km above the surface. Wind measurement campaigns are also conducted once per month for 5-10 orbits. These densities, temperatures and winds change with time (e.g. season, local time) and location, and sometimes fluctuate quickly. Global dust storm events are also known to significantly impact these density, temperature and wind fields in the Mars thermosphere. Such global dust storm period measurements can be compared to simulations from a computer model of the Mars atmosphere called M-GITM (Mars Global Ionosphere-Thermosphere Model), developed at U. of Michigan. This is the first detailed comparison between direct global dust storm period measurements in the upper atmosphere of Mars and simulated MGITM fields and is important because it can help to inform us what physical processes are acting on the upper atmosphere during such large dust events. Since the global circulation plays a role in the structure, variability, and evolution of the atmosphere, understanding the processes that drive the winds in the upper atmosphere of Mars also provides key context for understanding how the atmosphere behaves as a whole system. A basic version of the M-GITM code can be found on Github as follows: https:/github.com/dpawlows/MGITM and About 4 months of Neutral Gas and Ion Mass Spectrometer (NGIMS) measurements of densities and winds have been made by the MAVEN team during the summer of 2018 (Elrod et al., 2019). Nine reference measurement intervals during this global dust storm (1-June through 30-August 2018) are selected for detailed study (Elrod et al. 2019). The Mars conditions for these nine intervals have been used to launch corresponding M-GITM code simulations, yielding 3-D neutral density, temperature and wind fields for comparison to these NGIMS measurements. The M-GITM datacubes used to extract the density, temperature and neutral winds, along the trajectory of each orbit path between 140 and 240 km, are provided in this Deep Blue Data archive. README files are provided for each datacube, detailing the contents of each file. A general README file is also provided that summarizes the inputs and outputs of the M-GITM code simulations for this study.
- Keyword:
- Mars, MAVEN Spacecraft, Mars Thermosphere, and Mars Global Dust Storm of 2018
- Citation to related publication:
- Elrod, M. K., S. W. Bougher, K. Roeten, R. Sharrar, J. Murphy, Structural and Compositional Changes in the Upper Atmosphere related to the PEDE-2018 Dust Event on Mars as Observed by MAVEN NGIMS, Geophys. Res. Lett., (2019). doi: 10.1029/2019GL084378. and Jain, S. K., S. W. Bougher, J. Deighan, N. M. Schneider, F. Gonzalez-Galindo, A. I. F. Stewart, R. Sharrar, D. Kass, J. Murphy, and D. Pawlowski, Martian Thermospheric Warming Associated with the Planet Encircling Dust Storm Event of 2018, Geophys. Res. Lett., submitted (2019).
- Discipline:
- Engineering and Science
- Title:
- Mars Thermospheric Responses to a Global Dust Storm (PEDE-2018): Mars Global Ionosphere-Thermosphere Model (M-GITM) Simulated Datasets for Comparison to MAVEN Spacecraft Measurements
-
- Creator:
- Schiffmann, Philipp, Sick, Volker, and Reuss, David L
- Description:
- This archive contains data files from motored internal combustion engine experiments. Included are two-dimensional two-component velocity fields from four measurement planes with maximized field of view. in-cylinder pressure measurements, external pressure and temperature data, as well as details on the geometry of the optical engine to enable setups of simulation configurations. Motored operating conditions include 40kPa and 90kPa MAP, 800 and 1300 RPM.
- Keyword:
- TCC III engine, internal combustion engine, particle image velocimetry, in-cylinder flow, turbulence in engines, CFD validation data, motored engine, optical engine, cyclic variability , and PIV
- Citation to related publication:
- http://dx.doi.org/10.2516/ogst/2015028
- Discipline:
- Engineering
- Title:
- TCCIII Motored Full View
-
- Creator:
- Schiffmann, Philipp, Sick, Volker, and Reuss, David L
- Description:
- This archive contains data files from spark-ignited homogenous combustion internal combustion engine experiments. Included are two-dimensional two-component velocity fields acquired in a small, high-resolution field of view near the spark plug, and images of hydroxyl radical chemiluminescence recording the early flame-kernel growth. Included are in-cylinder pressure measurements, external pressure and temperature data, as well as details on the geometry of the optical engine to enable setups of simulation configurations. Included are tables of one-per-cycle parameters for each test with methane or propane at stoichiometric, dilute limit, lean limit, and rich limit, operation conducted at 40kPa and 1300 RPM.
- Keyword:
- OH* imaging, TCC III engine, internal combustion engine, particle image velocimetry, in-cylinder flow, turbulence in engines, CFD validation data, cyclic variability, early flame kernel growth, optical engine, combustion variability, ignition, and PIV
- Citation to related publication:
- dx.doi.org/10.1177/1468087417720558
- Discipline:
- Engineering
- Title:
- TCCIII Fired Spark Plug Region
-
- Creator:
- Schiffmann, Philipp, Sick, Volker, and Reuss, David L
- Description:
- This archive contains data files from spark-ignited homogenous combustion internal combustion engine experiments. Included are two-dimensional two-component velocity fields from various measurement planes with maximized field of view, in-cylinder pressure measurements, external pressure and temperature data, as well as details on the geometry of the optical engine to enable setups of simulation configurations. Fired operation was with stoichiometric propane air, 40kPa MAP, at 1300 RPM.
- Keyword:
- TCC III engine, internal combustion engine, particle image velocimetry, in-cylinder flow, turbulence in engines, CFD validation data, cyclic variability, optical engine, combustion variability, and PIV
- Citation to related publication:
- dx.doi.org/10.1177/1468087417720558
- Discipline:
- Engineering
- Title:
- TCCIII Fired Full View
-
- Creator:
- Skerlos, Steven J.
- Description:
- Supporting Information for research article "Life cycle comparison of environmental emissions from three disposal options for unused pharmaceutical". This spreadsheet provides the calculations and values used for this study; please refer to the manuscript and supporting information (as text) available at http://dx.doi.org/10.1021/es203987b for details about how to use this spreadsheet. We use life cycle assessment methodology to compare three disposal options for unused pharmaceuticals: (i) incineration after take-back to a pharmacy, (ii) wastewater treatment after toilet disposal, and (iii) landfilling or incineration after trash disposal. For each option, emissions of active pharmaceutical ingredients to the environment (API emissions) are estimated along with nine other types of emissions to air and water (non-API emissions). Under a scenario with 50% take-back to a pharmacy and 50% trash disposal, current API emissions are expected to be reduced by 93%. This is within 6% of a 100% trash disposal scenario, which achieves an 88% reduction. The 50% take-back scenario achieves a modest reduction in API emissions over a 100% trash scenario while increasing most non-API emissions by over 300%. If the 50% of unused pharmaceuticals not taken-back are toileted instead of trashed, all emissions increase relative to 100% trash disposal. Evidence suggests that 50% participation in take-back programs could be an upper bound. As a result, we recommend trash disposal for unused pharmaceuticals. A 100% trash disposal program would have similar API emissions to a take-back program with 50% participation, while also having significantly lower non-API emissions, lower financial costs, higher convenience, and higher compliance rates.
- Citation to related publication:
- Discipline:
- Engineering
- Title:
- Unused Pharmaceutical Disposal Model
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- Creator:
- Tsai, Grace and Kuipers, Benjamin
- Description:
- ******Michigan Indoor Corridor 2012 Dataset****** This dataset is made available for research purpose only. Please contact Grace Tsai( gstsai@umich.edu) for any questions or comments. This dataset was used to produce the results in our IROS 2012 paper. If you use the data, please cite the following reference in your publications related to this work: Grace Tsai and Benjamin Kuipers Dynamic Visual Understanding of the Local Environment for an Indoor Navigating Robot International Conference on Intelligent Robots and Systems (IROS'12) October 2012 The dataset contains 4 video sequences acquired with camera mounted on a wheeled vehicle. The camera was set-up so that there was zero tilt and roll angle with respect to the ground. The camera has a fixed height (0.47 m) with the ground throughout the video. The intrinsic parameters of the cameras are: Focal length fc = [ 1389.182714 1394.598277 ] Principal point cc = [ 672.605430 387.235803 ] The distortion of the camera has been corrected. For each video sequences, an estimated camera pose in each frame of the video is provided in the file pose.txt. Each line in the file looks like: <frame index> <x (pose)> <y (pose)> <theta (pose)> Note the camera poses provided here are estimated by using an occupancy grid mapping algorithm with a laser range finder to obtain the robot pose. The dataset provides a ground truth labeling for all the pixels every 10 frames for each video. The labels of each frame is stored as a 2D matrix in a .mat file. The filename of each .mat file corresponds to the image frame. The labels can be interpreted as followed: -2 -> ceiling plane -1 -> ground plane >0 -> walls The labels of the walls are illustrated in a .pdf figure. Note the figure is only a illustration graph, not an actual floor plan.
- Keyword:
- Robotics and Computer vision
- Citation to related publication:
- Grace Tsai and Benjamin Kuipers "Dynamic Visual Understanding of the Local Environment for an Indoor Navigating Robot" International Conference on Intelligent Robots and Systems (IROS'12) October 2012
- Discipline:
- Engineering
- Title:
- Michigan Indoor Corridor Dataset
-
- Creator:
- Figueroa, C. Alberto
- Description:
- Magnetic resonance angiography (MRA) of the aorta of a 30 yo healthy volunteer, segmented and discretized using the software CRIMSON ( www.crimson.software). Additionally, models corresponding to virtually-aged aortic geometries at ages: 40, 60, and 75.
- Keyword:
- Pulse Wave Velocity, Blood flow modeling, Hypertension, and Aging
- Citation to related publication:
- Cuomo F, Roccabianca S, Dillon-Murphy D, Xiao N, Humphrey JD, Figueroa CA (2017) Effects of age-associated regional changes in aortic stiffness on human hemodynamics revealed by computational modeling. PLoS ONE 12(3): e0173177. https://doi.org/10.1371/journal.pone.0173177
- Discipline:
- Engineering
- Title:
- Effects of Age-Associated Regional Changes in Aortic Stiffness on Human Hemodynamics Revealed by Computational Modeling
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- Creator:
- Larson, Ronald G., Wen, Fei, Huang, Wenjun, and Huang, Ming
- Description:
- We provide the parameters used in Umbrella Sampling simulations reported in our study "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method", namely the set positions and spring constants for each window in simulations. Two tables are provided. Table 1 lists the names of the peptides and their corresponding sequences. Table 2 lists the parameters. The abstract of our work is the following: We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with Weighted Histogram Analysis Method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse-grained (CG) force field (MARTINI) is less prone to significant error induced by biased-sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3-4 residue peptide segments while leaving the remain-ing peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and relia-bly estimate the binding free energy between an arbitrary peptide and an MHC class II molecule.
- Keyword:
- Molecular Dynamics, Binding Free Energy, Protein, MHC, and Coarse-Grained
- Citation to related publication:
- M. Huang, W. Huang, F. Wen, R. G. Larson. J. Comput. Chem. 2017, 38, 2007–2019. https://doi.org/10.1002/jcc.24845
- Discipline:
- Engineering and Science
- Title:
- Simulation Parameters used in the Study titled "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method"
-
- 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., 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.
- Discipline:
- Engineering
- Title:
- A Video-Based Intervention to Improve Belt Fit
-
- Creator:
- Grosky, William I. and Ruas, Terry L.
- Description:
- This dataset was used for a proof-of-concept of fixed lexical chain approach for semantic information retrieval.
- Keyword:
- fixed lexical chains
- Citation to related publication:
- Ruas, T. L., & Grosky, W. I. (2017). Exploring and expanding the use of lexical chains in information retrieval. Ann Arbor: University of Michigan. Retrieved from the Deep Blue institutional repository website: http://dx.doi.org/10.3998/2027.42/136659
- Discipline:
- Engineering
- Title:
- Semantic-Based Document Retrieval Using Spatial Distributions of Concepts
-
- Creator:
- Mathieu, Johanna L, Balzano, Laura, and Ledva, Gregory S
- Description:
- This data set contains the relevant time series for constructing and testing electricity load models within the related paper. The files within are a '.mat' file that contains the data and a 'readme.txt' file detailing the contents of the data.
- Keyword:
- Output feedback, Online learning, Machine learning, Real-time filtering, and Energy disaggregation
- Citation to related publication:
- https://arxiv.org/abs/1701.04389
- Discipline:
- Engineering
- Title:
- Data Files for Real-Time Energy Disaggregation of a Distribution Feeder's Demand
-
- Creator:
- Fries, Kevin J
- Description:
- This data is in support of the publication in review "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model". It is all the raw data extracted from the NWM flow forecasts for Iowa and the IFIS stage readings. For the NWM data, each date has it's own tab-delimited file with columns being the time (hrs) and rows being the NHD site. For the IFIS gages, each tab delimited file is for a single site for the period of record.
- Citation to related publication:
- Discipline:
- Engineering
- Title:
- Data for "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model"
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