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- Creator:
- Nguyen, Thanh H., Wright, Mason, Wellman, Michael P., and Singh, Satinder
- Description:
- In this work , we study the problem of allocating limited security countermeasures to protect network data from cyber-attacks, for scenarios modeled by Bayesian attack graphs. We consider multi-stage interactions between a network administrator and cybercriminals, formulated as a security game. We propose parameterized heuristic strategies for the attacker and defender and provide detailed analysis of their time complexity. Our heuristics exploit the topological structure of attack graphs and employ sampling methods to overcome the computational complexity in predicting opponent actions. Due to the complexity of the game, we employ a simulation-based approach and perform empirical game analysis over an enumerated set of heuristic strategies. Finally, we conduct experiments in various game settings to evaluate the performance of our heuristics in defending networks, in a manner that is robust to uncertainty about the security environment.
- Keyword:
- Empirical Game-Theoretic Analysis, Multi-stage Security Games, Attack Graph, Game Theory, and Moving Target Defense
- Citation to related publication:
- Nguyen, T. H., Wright, M., Wellman, M. P., & Singh, S. (2017). Multi-stage attack graph security games: Heuristic strategies, with empirical game-theoretic analysis. In MTD 2017 - Proceedings of the 2017 Workshop on Moving Target Defense, co-located with CCS 2017 (Vol. 2017-January, pp. 87-97). Association for Computing Machinery, Inc. https://doi.org/10.1145/3140549.3140562
- Discipline:
- Engineering and Science
- Title:
- Multi-Stage Attack Graph Security Games: Heuristic Strategies, with Empirical Game-Theoretic Analysis --- Dataset
-
- Creator:
- Isaacoff, Benjamin P., Li, Yilai, Lee, Stephen A., and Biteen, Julie S.
- Description:
- This is the experimental data referenced in our manuscript entitled “SMALL-LABS: An algorithm for measuring single molecule intensity and position in the presence of obscuring backgrounds .” These live-cell single-molecule imaging movies were used as a test of the SMALL-LABS single-molecule image analysis algorithm. The dataset comprises two movies; each one is provided both as a .tif stack and as an .avi file. The movie called “low_bg” has a standard low background, and the movie called “high_bg” includes a high fluorescent background produced by an external 488-nm laser.
- Keyword:
- single-molecule, microscopy, image analysis, mirobiology, and bacteria
- Citation to related publication:
- B.P. Isaacoff, Y. Li, S.A. Lee, J.S. Biteen, "SMALL-LABS: Measuring Single-Molecule Intensity and Position in Obscuring Backgrounds." Biophysical Journal, 975-982, 116, 2019. https://doi.org/10.1016/j.bpj.2019.02.006
- Discipline:
- Engineering and Science
- Title:
- Dataset of live-cell movies of single PolC-PAmCherry molecules in Bacillus subtilis cells with high and low fluorescent backgrounds.
-
- 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
- Discipline:
- Science and Engineering
- Title:
- Raw Rheology data in supplement to the 2019 Macromolecules publication: "Assessing the Range of Validity of Current Tube Models Through Analysis of a Comprehensive Set of Star-Linear 1,4-Polybutadiene Polymer Blends"
-
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:
- Engineering and Science
5Works -
- Creator:
- Crisp, Dakota N., Parent, Rachel, Nakatani, Mitsuyoshi, Murphy, Geoffrey G. , and Stacey, William C.
- Description:
- This data and scripts are meant to test and show that seizure onset dynamics can be modulated using anti-epileptic drugs. A zip file is included that contains all waveform data, MATLAB processing scripts, and metadata. The MATLAB scripts allow for visual review validation and objective feature analysis. The file includes various README files explaining the scripts and their relationships in greater detail.
- Keyword:
- Bifurcation, Epilepsy, Seizure, and Electrophysiology
- Discipline:
- Science, Engineering, and Health Sciences
- Title:
- Carbamazepine and GABA have distinct effects on seizure onset dynamics in mouse brain slices
-
- 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
- Title:
- Mars Thermospheric Neutral Winds: Mars Global Ionosphere-Thermosphere Model (M-GITM) Simulated Datasets for Comparison to MAVEN Spacecraft Measurements
-
- Creator:
- Stoev, Stilian and Hu, Weifeng
- Description:
- Many data sets come as point patterns of the form (longitude, latitude, time, magnitude). The examples of data sets in this format includes tornado events, origins/destination of internet flows, earthquakes, terrorist attacks and etc. It is difficult to visualize the data with simple plotting. This research project studies and implements non-parametric kernel smoothing in Python as a way of visualizing the intensity of point patterns in space and time. A two-dimensional grid M with size mx, my is used to store the calculation result for the kernel smoothing of each grid points. The heat-map in Python then uses the grid to plot the resulting images on a map where the resolution is determined by mx and my. The resulting images also depend on a spatial and a temporal smoothing parameters, which control the resolution (smoothness) of the figure. The Python code is applied to visualize over 56,000 tornado landings in the continental U.S. from the period 1950 - 2014. The magnitudes of the tornado are based on Fujita scale.
- Citation to related publication:
- Hu, Weifeng. “Kernel-based Visualization of Point Patterns in Python with Application to Tornado Landing Data.” (2016). At https://www.semanticscholar.org/paper/Kernel-based-Visualization-of-Point-Patterns-in-to-Hu/0de06a6db39da54fe28f8d0cb47c0d3270f2f831
- Discipline:
- Science and Engineering
- Title:
- Statistics and Visualization of Point-Patterns
-
- Creator:
- Mirshams Shahshahani, Payam
- Description:
- Investigating minimum human reaction times is often confounded by the motivation, training, and state of arousal of the subjects. We used the reaction times of athletes competing in the shorter sprint events in the Athletics competitions in recent Olympics (2004-2016) to determine minimum human reaction times because there's little question as to their motivation, training, or state of arousal. The reaction times of sprinters however are only available on the IAAF web page for each individual heat, in each event, at each Olympic. Therefore we compiled all these data into two separate excel sheets which can be used for further analyses.
- Keyword:
- minimum reaction time, sprinter, Olympics, Athletics, sex difference, starting block, and false start
- Citation to related publication:
- Mirshams Shahshahani P, Lipps DB, Galecki AT, Ashton-Miller JA (2018) On the apparent decrease in Olympic sprinter reaction times. PLoS ONE 13(6): e0198633. https://doi.org/10.1371/journal.pone.0198633
- Discipline:
- Science, General Information Sources, Engineering, Other, and Health Sciences
- Title:
- Downloaded IAAF Sprint Results in all Heats for 2004 - 2016 Olympics for both Men and Women
-
- Creator:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research
- Description:
- Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler, http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015., More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015: https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/, and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Smith, J., Gronewald, A. et al. Summary Report: Development of the Large Lake Statistical Water Balance Model for Constructing a New Historical Record of the Great Lakes Water Balance. Submitted to: The International Watersheds Initiative of the International Joint Commission. Accessible at https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf, Large Lake Statistical Water Balance Model (L2SWBM). https://www.glerl.noaa.gov/data/WaterBalanceModel/, and Gronewold, A.D., Smith, J.P., Read, L. and Crooks, J.L., 2020. Reconciling the water balance of large lake systems. Advances in Water Resources, p.103505.
- Discipline:
- Science and Engineering
- Title:
- Large Lake Statistical Water Balance Model - Laurentian Great Lakes - 1 month time window - 1980 through 2015 monthly summary data and model output
-
- Creator:
- Regoli, Leonardo H.
- Description:
- The research analyzed the response of nine PNI RM3100 magnetometers to radiation doses expected during a Europa lander mission. The radiation levels are drawn from the Europa Lander Science Definition Team report. The sensors were tested up to a total ionization dose (TID) level of 500 kRad.
- Keyword:
- Magnetometer, Magneto-inductive, Europa, and Radiation
- Discipline:
- Science and Engineering
- Title:
- Sensor data for "Radiation tolerance of the PNI RM3100 magnetometer for a Europa lander mission"
-
- Creator:
- Ramasubramani, Vyas
- Description:
- The goal of the work is to elucidate the stability of a complex experimentally observed structure of proteins. We found that supercharged GFP molecules spontaneously assemble into a complex 16-mer structure that we term a protomer, and that under the right conditions an even larger assembly is observed. The protomer structure is very well defined, and we performed simulations to try and understand the mechanics underlying its behavior. In particular, we focused on understanding the role of electrostatics in this system and how varying salt concentrations would alter the stability of the structure, with the ultimate goal of predicting the effects of various mutations on the stability of the structure. There are two separate projects included in this repository, but the two are closely linked. One, the candidate_structures folder, contains the atomistic outputs used to generate coarse-grained configurations. The actual coarse-grained simulations are in the rigid_protein folder, which pulls the atomistic coordinates from the other folder. All data is managed by signac and lives in the workspace directories, which contain various folders corresponding to different parameter combinations. The parameters associated with a given folder are stored in the signac_statepoint.json files within each subdirectory. The atomistic data uses experimentally determined protein structures as a starting point; all of these are stored in the ConfigFiles folder. The primary output is the topology files generated from the PDBs by GROMACS; these topologies are then used to parametrize the Monte Carlo simulations. In some cases, atomistic simulations were actually run as well, and the outputs are stored alongside the topology files. In the rigid_protein folder, the ConfigFiles folder contains MSMS, the software used to generate polyhedral representations of proteins from the PDBs in the candidate_structures folder. All of the actual polyhedral structures are also stored in the ConfigFiles folder. The actual simulation trajectories are stored as general simulation data (GSD) files within each subdirectory of the workspace, along with a single .pos file that contains the shape definition of the (nonconvex) polyhedron used to represent a protein. The logged quantities, such as energies and MC move sizes, are stored in .log files. The logic for the simulations in the candidate_structures project is in the Python scripts project.py, operations.py, and scripts/init.py. The rigid_protein folder also includes the notebooks directory, which contains Jupyter notebooks used to perform analyses, as well as the Python scripts used to actually perform the simulations and manage the data space. In particular, the project.py, operations.py and scripts/init.py scripts contain most of the logic associated with the simulations.
- Keyword:
- Protein assembly, Cryo TEM, Hierarchical Assembly, Monte Carlo simulation, and Coarse-grained simulation
- Citation to related publication:
- Anna J Simon, Vyas Ramasubramani, Jens Glaser, Arti Pothukuchy, Jillian Gerberich, Janelle Leggere, Barrett R Morrow, Jimmy Golihar, Cheulhee Jung, Sharon C Glotzer, David W Taylor, Andrew D Ellington,"Supercharging enables organized assembly of synthetic biomolecules," bioRxiv 323261; doi: https://doi.org/10.1101/323261
- Discipline:
- Science and Engineering
- Title:
- Simulation Data associated with the paper: Supercharging enables organized assembly of synthetic biomolecules
-
- Creator:
- Ayumi Fujisaki-Manome
- Description:
- Precipitation impacts on ice cover and water temperature in the Laurentian Great Lakes were examined using state-of-art coupled ice-hydrodynamic models. Numerical experiments were conducted for the recent anomalously cold (2014-2015) and warm (2015-2016) winters that were accompanied by high and low ice coverage over the lakes, respectively. The results of numerical experiments showed that, snow cover on the ice, which is the manifestation of winter precipitation, reduced the total ice volume (or mean ice thickness) in all of the Great Lakes, shortened the ice duration, and allowed earlier warming of water surface. The reduced ice volume was due to the thermal insulation of snow cover. The surface albedo was also increased by snow cover, but its impact on the delay the melting of ice was overcome by the thermal insulation effect. During major snowstorms, snowfall over the open lake caused notable cooling of the water surface due to latent heat absorption. Overall, the sensible heat flux from rain in spring and summer was found to have negligible impacts on the water surface temperature. Although uncertainties remain in over-lake precipitation estimates and model’s representation of snow on the ice, this study demonstrated that winter precipitation, particularly snowfall on the ice and water surfaces, is an important contributing factor in Great Lakes ice production and thermal conditions from late fall to spring.
- Keyword:
- Great Lakes, lake ice, numerical modeling, and precipitation
- Citation to related publication:
- Fujisaki-Manome, A., E.J. Anderson, J.A. Kessler, P.Y. Chu, J. Wang, and A.D. Gronewold, Simulating impacts of precipitation on ice cover and surface water temperature across large lakes, Journal of Geophysical Research Oceans, in revision.
- Discipline:
- Science and Engineering
- Title:
- FVCOM-UGCICE source codes and model results for assessment of precipitation impact on Great Lakes ice cover and water temperature
-
- 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:
- Science and Engineering
- 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:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research
- Description:
- Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler, http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015., More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015: https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/ , and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Smith, J., Gronewald, A. et al. Summary Report: Development of the Large Lake Statistical Water Balance Model for Constructing a New Historical Record of the Great Lakes Water Balance. Submitted to: The International Watersheds Initiative of the International Joint Commission. Accessible at https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf, Large Lake Statistical Water Balance Model (L2SWBM). https://www.glerl.noaa.gov/data/WaterBalanceModel/, and Gronewold, A.D., Smith, J.P., Read, L. and Crooks, J.L., 2020. Reconciling the water balance of large lake systems. Advances in Water Resources, p.103505.
- Discipline:
- Science and Engineering
- Title:
- Large Lake Statistical Water Balance Model - Laurentian Great Lakes - 6 month time window - 1980 through 2015 monthly summary data and model output
-
- Creator:
- James, David A. and Lokam, Nikhil
- Description:
- The object of this project is to provide researchers and students with a tool to allow them to develop an intuitive understanding of singular vectors and singular values. 2x2 matrices A with real entries map circles to ellipses; in particular, unit circles centered at the origin to ellipses centered at the origin. It is known that the points on the ellipse farthest from the origin correspond to the singular vectors of A. Users can use the GUI to enter matrices of their choice and explore to visually self-determine the singular vectors/values.
- Keyword:
- SVD, Singular Value Decomposition, Singular Vector, Singular Value, and Matrix
- Discipline:
- Science and Engineering
- Title:
- Self-Discovery Module (GUI) for Singular Vectors: The"Greatest Stretch" Method for 2x2 Matrices
-
- 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:
- Terry Ruas, Charles Henrique Porto Ferreira, William Grosky, Fabrício Olivetti de França, Débora Maria Rossi de Medeiros, "Enhanced word embeddings using multi-semantic representation through lexical chains", Information Sciences, 2020, https://doi.org/10.1016/j.ins.2020.04.048
- Discipline:
- Other, Engineering, and Science
- Title:
- Enhanced word embeddings using multi-semantic representation through lexical chains
-
- Creator:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research, University of Michigan
- Description:
- Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler, http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015., More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015: https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/, and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine Learning, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Smith, J., Gronewald, A. et al. Summary Report: Development of the Large Lake Statistical Water Balance Model for Constructing a New Historical Record of the Great Lakes Water Balance. Submitted to: The International Watersheds Initiative of the International Joint Commission. Accessible at https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf, Large Lake Statistical Water Balance Model (L2SWBM). https://www.glerl.noaa.gov/data/WaterBalanceModel/, and Gronewold, A.D., Smith, J.P., Read, L. and Crooks, J.L., 2020. Reconciling the water balance of large lake systems. Advances in Water Resources, p.103505.
- Discipline:
- Science and Engineering
- Title:
- Large Lake Statistical Water Balance Model - 12 month time window - 1980 through 2015 monthly summary data and model output
-
- 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., Bougher, S. W., Deighan, J., Schneider, N. M., Gonzalez‐Galindo, F., Stewart, A. I. F., et al. ( 2020). Martian thermospheric warming associated with the Planet Encircling Dust Event of 2018. Geophysical Research Letters, 47, e2019GL085302. https://doi.org/10.1029/2019GL085302
- Discipline:
- Science and Engineering
- 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
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- Creator:
- Gliske, Stephen V and Stacey, William C
- Description:
- This data is part of a large program to translate detection and interpretation of HFOs into clinical use. A zip file is included which contains hfo detections, metadata, and Matlab scripts. The matlab scripts analyze this input data and produce figures as in the referenced paper (note: the blind source separation method is stochastic, and so the figures may not be exactly the same). A file "README.txt" provides more detail about each individual file within the zip file.
- Keyword:
- hfo, high frequency oscillation, ripple, fast ripple, blind source separation, non-negative matrix factorization, and temporal variability
- Citation to related publication:
- Stephen V. Gliske, Zachary T. Irwin, Cynthia Chestek, Garnett L. Hegeman, Benjamin Brinkmann, Oren Sagher, Hugh J. L. Garton, Greg A. Worrell, William C. Stacey. "Variability in the location of High Frequency Oscillations during prolonged intracranial EEG recordings." Nature Communications. https://doi.org/10.1038/s41467-018-04549-2
- Discipline:
- Science, Engineering, and Health Sciences
- Title:
- Supporting data and scripts for the paper "Variability in the location of High Frequency Oscillations during prolonged intracranial EEG recordings"
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- Creator:
- Mukhopadhyay, Agnit, Daniel T Welling, Michael W Liemohn, Aaron J Ridley, Shibaji Chakrabarty, and Brian J Anderson
- Description:
- An updated auroral conductance module is built for global models, using nonlinear regression & empirical adjustments to span extreme events., Expanded dataset raises the ceiling of conductance values, impacting the ionospheric potential dB/dt & dB predictions during extreme events., and Application of the expanded model with empirical adjustments refines the conductance pattern, and improves dB/dt predictions significantly.
- Keyword:
- Space Weather Forecasting, Extreme Weather, Ionosphere, Magnetosphere, MI Coupling, Ionospheric Conductance, Auroral Conductance, Aurora, SWMF, SWPC, Nonlinear Regression, and dB/dt
- Citation to related publication:
- Mukhopadhyay, A., et al. (2020). Conductance Model for Extreme Events : Impact of Auroral Conductance on Space Weather Forecasts. Forthcoming.
- Discipline:
- Science and Engineering
- Title:
- Data Pertaining to Initial Simulations Using the Conductance Model for Extreme Events