Abstract: A large-scale radio frequency signal information processing and analysis system that provides advanced signal analysis for telecommunication applications, including band capacity and geographical density determinations and detection, classification, identification, and geolocation of signals across a wide range of frequencies and across broad geographical areas. The system may utilize a range of novel algorithms for bin-wise processing, Rayleigh distribution analysis, telecommunication signal classification, receiver anomaly detection, transmitter density estimation, transmitter detection and location, geolocation analysis, telecommunication activity estimation, telecommunication utilization estimation, frequency utilization estimation, and data interpolation.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.

Abstract: An example method comprises receiving first historical meso-scale numerical weather predictions (NWP) and power flow information for a geographic distribution area, correcting for overfitting of the historical NWP predictions, reducing parameters in the first historical NWP predictions, training first power flow models using the first reduced, corrected historical NWP predictions and the historical power flow information for all or parts of the first geographic distribution area, receiving current NWP predictions for the first geographic distribution area, applying any number of first power flow models to the current NWP predictions to generate any number of power flow predictions, comparing one or more of the any number of power flow predictions to one or more first thresholds to determine significance of reverse power flows, and generating a first report including at least one prediction of the reverse power flow and identifying the first geographic distribution area.

Abstract: Magnetic particle actuating systems may include a magnet system configured to generate a magnetic field that includes a field-free region. A corresponding control system can be configured to control the magnet system to create a field-free region at least partially matching a target region. An excitation system can be configured to generate an excitation field to cause actuation of magnetic nanoparticles in an actuation region.

Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: A method for creating a spatio-temporal schedule includes receiving a set of available work crews and a set of workorders to be scheduled, sequencing the set of workorders, wherein each workorder of the set of workorders is associated with a geographic location, a start time and an end time, and iterating through the set of available work crews, assigning a plurality of workorders of the set of workorders fully allocating a current crew before selecting a next crew, until all work crews are fully allocated and/or all workorders are assigned, wherein the assignment of workorders for a given work crew generates a route comprising the plurality of workorders.

Abstract: An example method comprises receiving historical sensor data of a first time period, the historical data including sensor data of a renewable energy asset, extracting features, performing a unsupervised anomaly detection technique on the historical sensor data to generate first labels associated with the historical sensor data, performing at least one dimensionality reduction technique to generate second labels, combining the first labels and the second labels to generate combined labels, generating one or more models based on supervised machine learning and the combined labels, receiving current sensor data of a second time period, the current sensor data including sensor data of the renewable energy asset, extracting features, applying the one or more models to the extracted features of the current sensor data to create a prediction of a future fault in the renewable energy asset, and generating a report including the prediction of the future fault in the energy asset.

Abstract: A system and method of managing a network with assets are described. The method includes generating a directed graph with each of the assets represented as a node, determining individual failure probability of each node, computing downstream failure probability of each node according to an arrangement of the nodes in the directed graph, computing upstream failure probability of each node according to the arrangement of the nodes in directed graph, and computing network failure probability for each node based on the corresponding individual failure probability, the downstream failure probability, and the upstream failure probability. Managing the network is based on the network failure probability of the assets.

Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.

Abstract: Methods, systems, and computer program products for dynamic pricing of energy consumed from a shared battery using real-time consumption data are provided herein. A computer-implemented method includes calculating wear cost arising from a battery shared by multiple users, wherein the wear cost is based on usage data of the battery; calculating a proportionality factor for each of the multiple users for the calculated wear cost, wherein the proportionality factor is based on individual usage of the battery; apportioning the calculated wear cost to each of the multiple users based on the user's proportionality factor; and determining a dynamic price for energy used by the battery for each of the multiple users, based on said apportioning.

Abstract: Conventional television audience measurements are made with diaries or by imaging the area in front of a television and trying to identify the people in the images watching television. Unfortunately, diaries are only accurate if the audience members record entries in them, and image-based techniques are intrusive. The present techniques address these problems by using a viewer's wearable device to measure a viewer's proximity to a television. The wearable device emits or receives low-power beacon signals; measurements of the signal strength are used to calculate the viewer's distance to the television. If the viewer is close enough to the television and the television is on, the viewer may be engaged with the content on the television. This system is simple, non-intrusive, and can used to measure engagement with each television in a multi-television household.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.

Abstract: A method for generating electric substation load transfer control parameters includes adjusting elements in a fundamental scale matrix according to a condition change of a power grid, wherein the fundamental scale matrix is constructed based on the topology structure of the power grid, and the elements in the fundamental scale matrix represent switch information and risk values of paths between nodes of the power grid, wherein the switch information represents number of switching times required for connecting two nodes of the power grid; and performing operations on the adjusted fundamental scale matrix to generate switch information and risk values of paths for electric substation load transfer control, as electric substation load transfer control parameters.

Abstract: Systems and methods for fast and efficient retrieval of NFT ownership information are provided. An exemplary method includes initializing a mirror blockchain by making a copy of an NFT blockchain; initializing an ownership transaction table and an NFT ledger from a mirror NFT blockchain by processing the mirror blockchain from a beginning block to an end block; periodically update the mirror blockchain with new blocks from an NFT blockchain thereby forming a new end block; processing ownership transaction events that modify NFT ownership in the new blocks up to a fixed offset from the new end block; updating the ownership transaction table; updating the NFT ledger; receiving a request for all NFTs owned by a crypto-wallet address; generating a response with the NFTs owned by the crypto-wallet address from the NFT ledger; selecting an NFT group; and verifying the NFT ledger against the NFT blockchain ownership.

Abstract: A large-scale radio frequency signal collection and processing system comprising a plurality of sensor systems mounted on a plurality of collection platforms that integrates a plurality of overlapping datasets with differing characteristics (e.g., different resolutions, different view angles, different heights, different time periods, unrelated types of data) to generate an enriched dataset or datasets using a variety of processing techniques (e.g., statistical analysis, signal processing, image processing) that allows for more comprehensive analysis of the radio frequency signal landscape than would be possible using any of the datasets individually, or in combination but without such integration.

Abstract: Systems and methods for intelligent and adaptive testing of a blockchain application to identify compliant code modifications. The method includes the steps of recording requests to and response from a baseline blockchain application receiving the requests from a plurality of application users. The same responses are input into a shadow blockchain application that includes a number of switch selectable new code segments. The switch selectable new code is enabled and disabled according to a pattern. The responses from the baseline application are compared against the response from the shadow blockchain application from when error vectors are generated. These error vectors are used to train a learning machine to determine which new code segments result in response errors or aberrations.

Abstract: Systems and methods for improving reliability in blockchain networks using sharding are disclosed herein. An example method includes assigning a unique identifier to a user, applying a deterministic function, such as a consistent hashing algorithm, to the unique identifier to select a unique set of nodes that are assigned to a shard for the user, wherein the nodes are a subset of available nodes, receiving a request for blockchain data from the user, generating a response to the request using a consistent view of a blockchain obtained from the unique set of nodes, and transmitting the response to the request to the user.

Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.

Abstract: An example method comprises receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.

Abstract: An exemplary method includes solving on a computing system an optimal power flow formulation for a plurality of generators in a power system. The solving includes computing using multi-threaded parallelism a plurality of constraints for the formulation, computing using multi-threaded parallelism a plurality of Jacobian functions of the constraints, and computing using multi-threaded parallelism a Hessian of Lagrangian functions. The method further includes outputting results of the solving, wherein the results comprise values of generation levels for the plurality of generators. Apparatus and program products are also disclosed.