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: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: An example method comprises receiving first historical data of a first time period and failure data, identifying at least some sensor data that was or potentially was generated during a first failure, removing the at least some sensor data to create filtered historical data, training a classification model using the filtered historical data, the classification model indicating at least one first classified state at a second period of time prior to the first failure indicated by the failure data, applying the classification model to second sensor data to identify a first potential failure state based on the at least one first classified state, the second sensor data being from a subsequent time period, generating an alert if the first potential failure state is identified based on at least a first subset of sensor signals generated during the subsequent time period, and providing the alert.

Abstract: Technical solutions are described for forecasting leaks in a pipeline network. An example method includes identifying a subsystem in the pipeline network that includes a first station. The method also includes accessing historical temporal sensor measurements of the stations. The method also includes generating a prediction model for the first station that predicts a pressure measurement at the first station based on the historical temporal sensor measurements at each station in the subsystem. The method also includes predicting a series of pressure measurements at the first station based on the historical temporal sensor measurements. The method also includes determining a series of deviations between the series of pressure measurements and historical pressure measurements of the first station and identifying a threshold value from the series of deviations, where a pressure measurement at the first station above or below the threshold value is indicative of a leak in the subsystem.

Abstract: A system and method for detecting and identifying emitted electromagnetic signals, comprising wideband radio frequency sensors, at least one wide band radio frequency receiving antenna and accompanying electronics, a platform for hosting multiple antennas and sensor mounts, and processing algorithms for detection and identification of electromagnetic (EM) signals. Various algorithms and implementations are employed to detect and identify, over a wide frequency range, narrow or wide bandwidth EM signals having low signal levels, time-varying, and/or time-intermittent characteristics.

Abstract: Systems and methods for precomputing data and storing cache objects corresponding to the precomputed data are described. A system creates a new cache object when a user interacts with the system. The system precomputes formulas in the newly created cache object by replacing the formulas with corresponding calculated values. The system precomputes the formulas in the background (i.e., the user is not presented with the precomputed values while the user is manipulating the data). The system may persistently store a precomputed version cache object in a dedicated version cache storage for later use. If updates are performed to the structure and/or values of a version represented in a precomputed version cache object, effected parts of the version cache object are invalidated by replacing calculated values with the underlying formulas.

Abstract: Disclosed is a method and system for processing images from an aerial imaging device. An image of an object of interest is received from the aerial imaging device. A parameter vector is extracted from the image. Image analysis is performed on the image to determine a height and a width of the object of interest. Idealized images of the object of interest are generated using the extracted parameter vector, the determined height, and the determined width of the object of interest. Each idealized image corresponds to a distinct filled volume of the object of interest. The received image of the object of interest is matched to each idealized image to determine a filled volume of the object of interest. Information corresponding to the determined filled volume of the object of interest is transmitted to a user device.

Abstract: The present invention proposes a lightning forecast method, comprising: identifying a Targeted Weather of SDA carrier (TWLC) based on radar reflectivity data; forecasting a future TWLC state based on the identified TWLC; building or updating an SDA model based on SDA observation data and detected TWLC state-related data; and calculating the probability of producing SDA in the forecasted future TWLC according to the SDA model.

Abstract: The present invention proposes a lightning forecast method, comprising: identifying a Targeted Weather of SDA carrier (TWLC) based on radar reflectivity data; forecasting a future TWLC state based on the identified TWLC; building or updating an SDA model based on SDA observation data and detected TWLC state-related data; and calculating the probability of producing SDA in the forecasted future TWLC according to the SDA model.

Abstract: A medical imaging system for detecting ionizing radiation. The system includes one or more pixilated imagers positioned to acquire patient image data and one or more position sensors positioned to acquire patient position data. Once the patient image data and patient position data are acquired, one or more processors operably connected to each of the one or more pixilated imagers and one or more position sensors calculate a three-dimensional mass distribution based on patient image data and patient position data.

Abstract: Disclosed is a method and system for processing images from an aerial imaging device. A moving vehicle analysis system receives images from an aerial imaging device. The system may perform edge analysis in the images to identify a pairs of edges corresponding to a road. The system may identify pixel blobs in the images including adjacent pixels matching each other based on a pixel attribute. The system uses a machine learning model for generating an output identifying moving vehicles in the images. The system determines a count of the moving vehicles captured by the images, where each moving vehicle is associated with corresponding pixel blobs.

Abstract: Various embodiments manage energy generation in a power generation and distribution system. In one embodiment, a set of residual load data is obtained for a given period of time measured at one or more nodes within a power generation and distribution system. The set of residual load data encodes a set of power flow signals. The set of residual load data is analyzed. An amount of power contributed to the set of residual load data by at least one energy generator class is determined based on the analysis of the set of residual load data.

Abstract: Techniques for generating an instrumented software package and executing an instance thereof are disclosed. A software package, such as a container image, includes a library of system call wrapper functions. An instrumented system call wrapper function includes (a) a corresponding system call wrapper function and (b) instrumentation code. Instrumentation code is configured to perform one or more of: (a) capturing data associated with executing the set of operations associated with requesting the system call, and (b) manipulating execution of the set of operations associated with requesting the system call. An instrumented library, including instrumented system call wrapper functions, is added to the software package to generate an instrumented software package. An instrumentation configuration is applied to an instance of the instrumented software package.

Abstract: A method and apparatus for forecasting output power of wind turbine in a wind farm. The present invention provides a method for forecasting output power of a wind turbine in a wind farm, including: generating a corrected data set based on environmental data collected from at least one sensor in the wind farm; correcting a weather forecasting model by using the corrected data set; obtaining a forecast value of wind information at the wind turbine based on the corrected weather forecasting model; and forecasting the output power of the wind turbine based on the forecast value and a power forecasting model.

Abstract: Disclosed is a method and system for processing images from an aerial imaging device. The method includes receiving a first image of a geographical area having a first resolution. The method transmits the first image to a machine learning model to identify an area of interest containing an object of interest. The method receives a second image of the geographical area having a second resolution higher than the first resolution. The method transmits the second image to the machine learning model to determine a likelihood that the area of interest contains the object of interest. The method trains the machine learning model to filter out features corresponding to the area of interest in images having the first resolution if the likelihood is below a threshold. The method transmits a visual representation of the object of interest to a user device if the likelihood exceeds the threshold.

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: The present invention provides a system and method for producing hydrocarbons from biomass. The method is particularly useful for producing substitute natural gas from forestry residues. Certain disclosed embodiments convert a biomass feedstock into a product hydrocarbon by fast pyrolysis. The resulting pyrolysis gas is converted to the product hydrocarbon and carbon dioxide in the presence of hydrogen and steam while simultaneously generating the required hydrogen by reaction with steam under prescribed conditions for self-sufficiency of hydrogen. Methane is a preferred hydrocarbon product. A system also is disclosed for cycling the catalyst between steam reforming, methanation and regeneration zones.

Abstract: Disclosed is a method and system for processing images from an aerial imaging device. The method includes receiving a first image of a geographical area having a first resolution. The method transmits the first image to a machine learning model to identify an area of interest containing an object of interest. The method receives a second image of the geographical area having a second resolution higher than the first resolution. The method transmits the second image to the machine learning model to determine a likelihood that the area of interest contains the object of interest. The method trains the machine learning model to filter out features corresponding to the area of interest in images having the first resolution if the likelihood is below a threshold. The method transmits a visual representation of the object of interest to a user device if the likelihood exceeds the threshold.

Abstract: In some embodiments, a non-transitory processor-readable medium stores code representing instructions that when executed cause a processor to select a narrative content template based at least in part on a predetermined content type associated with a real-world and/or virtual event. The code further represents instructions that when executed cause the processor to select a narrative tone type. The code further represents instructions that when executed cause the processor to, for each phrase included in an ordered set of phrases associated with the narrative content template, select, based at least in part on the narrative tone type, a phrase variation from a set of phrase variations associated with that phrase, and define, based on the selected phrase variation and at least one datum from a set of data, a narrative content portion associated with the real-world event. The code further represents instructions that when executed cause the processor to output, at a display, the narrative content portion.