Abstract: The protection of water providing entities from loss due to environmental events is disclosed including receiving structured and unstructured data related to a water resource, generating time series for a plurality of index items, generating training data and testing data based on the time series for the plurality of index items, determining correlations between the time series of the index items using the generated training data, determining a classification boundary as a strike level based on the determined correlation, generating a protection strategy based on the strike level, applying the protection strategy to the testing data to generate a resulting data time series, and presenting the resulting data time series via a display of a computing device to at least one user of the computing device.

Abstract: Embodiments of the invention are directed to computer-implemented methods, computer systems, and computer program products for monitoring the ergonomics of a user. A non-limiting example method includes capturing a reference image of the user using an image capture device. The method further includes determining a first height of an object of interest of the user using the reference image of the user. The method further includes capturing a subsequent image of the user using the image capture device. The method further includes determining a second height of the object of interest of the user using the subsequent image of the user. Based at least in part on determining that the second height is not within a first tolerance of the first height, causing the issuance of a warning that the user is not within an optimal distance from the image capture device.

Abstract: Embodiments of the invention are directed to computer-implemented methods, computer systems, and computer program products for monitoring the ergonomics of a user. A non-limiting example method includes capturing a reference image of the user using an image capture device. The method further includes determining a first height of an object of interest of the user using the reference image of the user. The method further includes capturing a subsequent image of the user using the image capture device. The method further includes determining a second height of the object of interest of the user using the subsequent image of the user. Based at least in part on determining that the second height is not within a first tolerance of the first height, causing the issuance of a warning that the user is not within an optimal distance from the image capture device.

Abstract: A distributed computer system includes a distributed processor, a distributed memory, and a simulation engine (SE). The SE includes a simulation I/O coupler that links a first variable of a first simulation model I/O data structure to a second variable of a second simulation model I/O data structure. The SE includes a natural language processing system that extracts a first variable description associated with the first variable, determines similar character strings to the first variable description from an information corpus, and ranks the determined character strings based upon similarity to the first variable description. The SE links the first variable to the second variable if the rank of an equal character string to the second variable description is greater than a rank threshold. The SE may augment the simulation model I/O data structures by writing a value of the first variable to a value of the second variable, or visa versa.

Abstract: Embodiments for managing aquatic infrastructure by one or more processors are described. A vehicle is detected within a vicinity of an aquatic infrastructure device. A wireless capability level of the vehicle is determined. Based on the determined wireless capability level of the vehicle, at least one of a wireless power transfer between the vehicle and the aquatic infrastructure device or a wireless data transfer between the vehicle and the aquatic infrastructure device is enabled.

Abstract: A distributed computer system includes a distributed processor, a distributed memory, and a simulation engine (SE). The SE includes a simulation I/O coupler that links a first variable of a first simulation model I/O data structure to a second variable of a second simulation model I/O data structure. The SE includes a natural language processing system that extracts a first variable description associated with the first variable, determines similar character strings to the first variable description from an information corpus, and ranks the determined character strings based upon similarity to the first variable description. The SE links the first variable to the second variable if the rank of an equal character string to the second variable description is greater than a rank threshold. The SE may augment the simulation model I/O data structures by writing a value of the first variable to a value of the second variable, or visa versa.

Abstract: Embodiments for intelligent forecasting of material concentrations in a fluid by a processor in a computing environment. A material concentration of a material in a fluid may be predicted according to one or more continuous stirred tank reactor (CSTR) surrogate models on statistical flow trajectories of the fluid defined by a principle component analysis (PCA) operation of a system.

Abstract: A fluid is modeled as a set of discrete particles. Each of the particles is associated with one or more properties, and a spatial distance comprising a smoothing length over which the one or more properties are to be smoothed. A corresponding trajectory is simulated for each of the particles. The corresponding trajectory is used to formulate a first solution for simulating transport within the fluid. A first predicted error is determined for the first solution. An iterative adjustment is performed to at least one of: a quantity of particles, the smoothing length, or the one or more corresponding properties, to formulate a second solution for simulating transport with the fluid, and a second predicted error is determined for the second solution, until the second predicted error is within a predefined boundary.

Abstract: Embodiments for estimating ice formation and depth by a processor. Ice formation and ice depth of a selected region of water may be cognitively forecasted using a prediction model such that the prediction model identifies similar characteristics between the selected region of water and one or more alternative regions of water by analyzing content of one or more data sources associated with an ontology of concepts representing a domain knowledge related to the selected region of water and the one or more alternative regions.

Abstract: Embodiments for providing aquatic epidemic alerts by a processor are described. Information associated with an aquatic epidemic in a body of water is received. A threat level associated with the aquatic epidemic for a location within the body of water is determined based on the information associated with the aquatic epidemic and water flow data associated with the body of water. An indication of the threat level is generated.

Abstract: Embodiments for managing aquatic infrastructure by one or more processors are described. A vehicle is detected within a vicinity of an aquatic infrastructure device. A wireless capability level of the vehicle is determined. Based on the determined wireless capability level of the vehicle, at least one of a wireless power transfer between the vehicle and the aquatic infrastructure device or a wireless data transfer between the vehicle and the aquatic infrastructure device is enabled.

Abstract: A mechanism is provided in a data processing system for minimizing uncertainty envelopes in trajectories of evolving ensemble members. The mechanism generates a trajectory forecast of each member object of an ensemble based on an initial state-space and a model for predicting trajectories of the member objects to generate a plurality of trajectory forecasts. Each of the plurality of trajectory forecasts has an individual uncertainty envelope. The mechanism applies a classification algorithm on the plurality of trajectory forecasts to identify at least one group of member objects having similar trajectory forecasts, generates a reduced ensemble of member objects including the identified group of member objects, and reconfigures the state-space and the model for predicting trajectories. The mechanism generates an updated trajectory forecast of each member object of the reduced ensemble based on the reconfigured state-space and the reconfigured model for predicting trajectories of the member objects.

Abstract: A computer system, method, and computer readable product are provided for cognitive initialization of large-scale advection-diffusion models. In various embodiments, parameters are identified for configuring an advection-diffusion model to be run. Then a natural language processing search is conducted for these parameters in relevant literature to find corresponding numerical values. These search results are compared, and values for the parameters are set for the advection-diffusion model, and the model is run.

Abstract: Embodiments for providing aquatic epidemic alerts by a processor are described. Information associated with an aquatic epidemic in a body of water is received. A threat level associated with the aquatic epidemic for a location within the body of water is determined based on the information associated with the aquatic epidemic and water flow data associated with the body of water. An indication of the threat level is generated.

Abstract: A mechanism is provided in a data processing system for minimizing uncertainty envelopes in trajectories of evolving ensemble members. The mechanism generates a trajectory forecast of each member object of an ensemble based on an initial state-space and a model for predicting trajectories of the member objects to generate a plurality of trajectory forecasts. Each of the plurality of trajectory forecasts has an individual uncertainty envelope. The mechanism applies a classification algorithm on the plurality of trajectory forecasts to identify at least one group of member objects having similar trajectory forecasts, generates a reduced ensemble of member objects including the identified group of member objects, and reconfigures the state-space and the model for predicting trajectories. The mechanism generates an updated trajectory forecast of each member object of the reduced ensemble based on the reconfigured state-space and the reconfigured model for predicting trajectories of the member objects.

Abstract: A computer-implemented method for configuring an advection diffusion model may include retrieving, via a processor, a plurality of advection diffusion model parameters indicative of model extremes of the advection diffusion model, retrieving, via the processor, convergence area information indicative of a convergence area for the advection diffusion model, determining, via the processor, an accuracy metric for each of the plurality of advection diffusion model parameters, selecting, via the processor, an optimal advection diffusion model parameter from the plurality of advection diffusion model parameters, and configuring, via the processor, the advection diffusion model with the optimal advection diffusion model parameter.

Abstract: A mechanism is provided for targeted, iterative refinement of advection-diffusion model grid resolution. A simulation is executed of advection-diffusion processes for an area associated with a user-defined location. Responsive to detecting an event within a subset of cells of a first set of cells, the subset of cells is refitted such that each of the subset of cells is gridded to comprise a second set of cells with dimensions less than the first set of cells. A number of run-time floating-point operations per second (FLOPS) of the model is computed for each of the first set of cells and the second set of cells. Based on a collective time associated with a computed number of FLOPS failing to exceed the user-defined constraint, the simulation continues to execute with the first set of cells and the second set of cells. The process is repeated until a predetermined resolution value is met.

Abstract: A computer-implemented method for configuring an advection diffusion model may include retrieving, via a processor, a plurality of advection diffusion model parameters indicative of model extremes of the advection diffusion model, retrieving, via the processor, convergence area information indicative of a convergence area for the advection diffusion model, determining, via the processor, an accuracy metric for each of the plurality of advection diffusion model parameters, selecting, via the processor, an optimal advection diffusion model parameter from the plurality of advection diffusion model parameters, and configuring, via the processor, the advection diffusion model with the optimal advection diffusion model parameter.

Abstract: A system, method and computer program product for determining an accuracy of a reconstructed image relative to a reference image. The method includes decomposing a reference image into a plurality of basis functions; reconstructing the image using the plurality of basis functions; determining differences between the reference image and reconstructed image; using statistical parametric mapping (SPM) to quantify existence of statistically significant regions of excursion in the determined differences; determining, based on the quantified regions of excursion, a minimum number of basis functions to reconstruct the image; and storing the determined number. The difference image is used as input to a univariate statistical test at every pixel to calculate an image of the test statistic which is then modeled as a multiGaussian random field.

Abstract: A computer-implemented method includes calculating, by a processor of a computer system, a value for a turbulent flow parameter in a simulated model comprising an initial turbulent flow scheme for an advection-diffusion process; determining, by the processor of the computer system, that the value for the turbulent flow parameter has exceeded a predetermined threshold; conducting, by the processor of the computer system, a search to identify search results for other turbulent flow schemes which match the value of the turbulent flow parameter; determining, by the processor of the computer system, a quantified level of information confidence for the search results; annotating, by the processor of the computer system, the search results with the quantified level of information confidence; and selecting, by the processor of the computer system, a new turbulent flow scheme corresponding to the search result having the highest quantified level of information confidence.