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Estimates of the water balance of the Laurentian Great Lakes using the Large Lakes Statistical Water Balance Model (L2SWBM)
User Collection
- Creator:
- Smith, Joeseph P., Fry, Lauren M., Do, Hong X., and Gronewold, Andrew D.
- Description:
- This collection contains estimates of the water balance of the Laurentian Great Lakes that were produced by the Large Lakes Statistical Water Balance Model (L2SWBM). Each data set has a different configuration and was used as the supplementary for a published peer-reviewed article (see "Citations to related material" section in the metadata of individual data sets). The key variables that were estimated by the L2SWBM are (1) over-lake precipitation, (2) over-lake evaporation, (3) lateral runoff, (4) connecting-channel outflows, (5) diversions, and (6) predictive changes in lake storage. and Contact: Andrew Gronewold Office: 4040 Dana Phone: (734) 764-6286 Email: drewgron@umich.edu
- Keyword:
- Great Lakes water levels, statistical inference, water balance, data assimilation, Great Lakes, Laurentian, Machine learning, Bayesian, and Network
- Citation to related publication:
- Smith, J. P., & Gronewold, A. D. (2017). Development and analysis of a Bayesian water balance model for large lake systems. arXiv preprint arXiv:1710.10161., Gronewold, A. D., Smith, J. P., Read, L., & Crooks, J. L. (2020). Reconciling the water balance of large lake systems. Advances in Water Resources, 103505., and Do, H.X., Smith, J., Fry, L.M., and Gronewold, A.D., Seventy-year long record of monthly water balance estimates for Earth’s largest lake system (under revision)
- Discipline:
- Science and Engineering
5Works -
- Creator:
- Malik, Hafiz and Khan, Muhammad Khurran, King Saud University
- Description:
- Details of the microphone used for data collection, acoustic environment in which data was collected, and naming convention used are provided here. 1 - Microphones Used: The microphones used to collect this dataset belong to 7 different trademarks. Table (1) illustrates the number of used Mics of different trademarks and models. Table 1: Trademarks and models of Mics Mic Trademark Mic Model # of Mics Shure SM-58 3 Electro-Voice RE-20 2 Sennheiser MD-421 3 AKG C 451 2 AKG C 3000 B 2 Neumann KM184 2 Coles 4038 2 The t.bone MB88U 6 Total 22 2- Environment Description: A brief description of the 6 environments in which the dataset was collected is presented here: (i) Soundproof room: a small room (nearly 1.5m × 1.5m × 2m), which is closed and completely isolated. With an exception of a small window in the front side of the room which is made of glass, all the walls of the room are made of wood and covered by a layer of sponge from the inner side, and the floor is covered by carpet. (ii) Class room: standard class room (6m × 5m × 3m). (iii) Lab: small lab (4m × 4m × 3m). All the walls are made of glasses and the floor is covered by carpet. The lab contains 9 computers. (iv) Stairs: is in the second floor. The place of recording is 3m × 5m (v) Parking: is the college parking. (vi) Garden: is an open space outside the buildings. 3- Naming Convention: This set of rules were followed as a naming convention to give each file in the dataset a unique name: (i) The file name is 19 characters long, and consists of 5 sections separated by underscores. (ii) The first section is of 3 characters indicates the Microphone trademark. (iii) The second section of 4 characters indicates the microphone model as in table (2). (iv) The third section of 2 characters indicates a specific microphone within a set of microphones of the same trademark and model, since we have more than one microphone of the same trademark and model. (v) The fourth section of 2 characters indicates the environment, where Soundproof room --> 01 Class room --> 02 Lab --> 03 Stairs --> 04 Parking --> 05 Garden --> 06 (vi) The fifth section of 2 characters indicates the language, where Arabic --> 01 English --> 02 Chinese --> 03 Indonesian --> 04 (vii) The sixth section of 2 characters indicates the speaker. Table 2: Microphones Naming Criteria Original Mic Trademark and model --> Naming Convenient Shure SM-58 --> SHU_0058 Electro-Voice RE-20 --> ELE_0020 Sennheiser MD-421 --> SEN_0421 AKG C 451 --> AKG_0451 AKG C 3000 B --> AKG_3000 Neumann KM184 --> NEU_0184 Coles 4038 --> COL_4038 The t.bone MB88U --> TBO_0088 For example: SEN_0421_02_01_02_03 is an English file recorded by speaker number 3 in the soundproof room using microphone number 2 of Sennheiser MD-421
- Keyword:
- audio forensic, multimedia forensics, microphone identification, tamper detection, splicing detection, and codec identification
- Citation to related publication:
- Muhammad Khurram Khan, Mohammed Zakariah, Hafiz Malik & Kim-Kwang Raymond Choo (2018). A novel audio forensic data-set for digital multimedia forensics, Australian Journal of Forensic Sciences, 50:5, 525-542, http://dx.doi.org/10.1080/00450618.2017.1296186
- Discipline:
- Engineering, Government, Politics and Law, and Science
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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., Bougher, S. W., Benna, M., Mahaffy, P. R., Lee, Y., Pawlowski, D., et al. (2019). MAVEN/NGIMS thermospheric neutral wind observations: Interpretation using the M‐GITM general circulation model. Journal of Geophysical Research: Planets, 124, 3283– 3303. https://doi.org/10.1029/2019JE005957
- Discipline:
- Science and Engineering
-
- 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:
- Saggio, M.L., Crisp, D., Scott, J., Karoly, P.J., Kuhlmann, L., Nakatani, M., Murai, T., Dümpelmann, M., Schulze-Bonhage, A., Ikeda, A., Cook, M., Gliske, S.V., Lin, J., Bernard, C., Jirsa, V., Stacey, W., 2020. In pre-print. Epidynamics characterize and navigate the map of seizure dynamics. bioRxiv 2020.02.08.940072. https://doi.org/10.1101/2020.02.08.940072
- Discipline:
- Engineering, Science, and Health Sciences
-
- Creator:
- Moniri, Saman and Shahani, Ashwin J.
- Description:
- The data is comprised of 20 .hdf files of the X-ray projections recorded during isothermal annealing of Zn-Mg samples, at discrete time-steps shown below for files names ending in ‘...30141’ to ‘…30161’: 30141: prior to annealing; 30142: 1 min annealing; 30143: 3 min; 30144: 5 min; 30145: 7 min; 30146: 10 min; 30147: 15 min; 30148: 20 min; 30150: 31 min; 30151: 1 hr; 30152: 2 hr; 30153: 3 hr; 30154: 4 hr; 30155: 5 hr; 30156: 6 hr; 30157:7 hr; 30158: 8 hr; 30159:9 hr; 30160: 9 hr, 10 min; 30161: 10 hr The raw data file is in .hdf format and can be reconstructed into .tiff, e.g., by using the TomoPy toolbox in Python.
- Keyword:
- Spiral eutectics
- Discipline:
- Engineering
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- Creator:
- Hall, Ryan J. and Larson, Ronald G.
- Description:
- This is data is a large assortment of over 50 1,4-polybutadiene star-linear blends that can be used for assessing and developing predictive models. The data are presented in CSV files.
- Keyword:
- polymers, rheology, star-linear polymer blends, and shear rheology
- Citation to related publication:
- Hall, R., Desai, P. S., Kang, B.-G., Huang, Q., Lee, S., Chang, T., Venerus, D. C., Mays, J., Ntetsikas, K., Polymeropoulos, G., Hadjichristidis, N., & Larson, R. G. (2019). Assessing the Range of Validity of Current Tube Models through Analysis of a Comprehensive Set of Star–Linear 1,4-Polybutadiene Polymer Blends. Macromolecules, 52(20), 7831–7846. https://doi.org/10.1021/acs.macromol.9b00642
- Discipline:
- Science and Engineering
-
- 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:
- Yao, M., Molzahn, D. K., & Mathieu, J. L. (2019). An Optimal Power-Flow Approach to Improve Power System Voltage Stability Using Demand Response. IEEE Transactions on Control of Network Systems, 6(3), 1015–1025. https://doi.org/10.1109/TCNS.2019.2910455, Yao, M., Mathieu, J. L., & Molzahn, D. K. (2017). Using demand response to improve power system voltage stability margins. 2017 IEEE Manchester PowerTech, 1–6. https://doi.org/10.1109/PTC.2017.7980798 , Koorehdavoudi, K., Yao, M., & Mathieu, J. (2017). Using Demand Response to Shape the Fast Dynamics of the Bulk Power Network. https://www.semanticscholar.org/paper/Using-Demand-Response-to-Shape-the-Fast-Dynamics-of-Koorehdavoudi-Yao/6799c161744c29e7603e3601daa284ecc84788a8, Yao, M., Hiskens, I. A., & Mathieu, J. L. (2018). Improving Power System Voltage Stability by Using Demand Response to Maximize the Distance to the Closest Saddle-Node Bifurcation. 2018 IEEE Conference on Decision and Control (CDC), 2390–2395. https://doi.org/10.1109/CDC.2018.8619091 , and Yao, M., Molzahn, D. K., & Mathieu, J. L. (2017). The impact of load models in an algorithm for improving voltage stability via demand response. 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 149–156. https://doi.org/10.1109/ALLERTON.2017.8262731
- Discipline:
- Engineering
-
- 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
- Discipline:
- Engineering
-
- 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
- Discipline:
- Engineering
-
- 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
- Discipline:
- Science and Engineering