Abstract: A method of sharing a wager on a live sporting event with another individual on a play by play wagering platform. Users can additionally invite other users to place the same wager or another wager on a different play. Upon accepting a wager invitation, the users additionally joining a chat conversation so as to communicate while placing wagers on the live sporting event.

Abstract: A method, system, and apparatus for generating probabilities, for example for displaying on a video feed, which may be generated or adjusted using machine learning and/or artificial intelligence. One embodiment includes a method for generating and adjusting probabilities. the generated probabilities in order to create and display probability graphics on a display device. The graphics may be generated and/or updated using artificial intelligence or machine learning. Display information may be updated in real-time as changes are made in the game (e.g. a player injury, substitutions, changing weather conditions, etc.). The changes may be detected by a detection system on the field, attached to players or equipment.

Abstract: A method of identifying wagers trends from a user's wagering history in order to alert the user of similar wagers that are available. The user interacts with a betting platform which displays all of the live plays available to be wagered upon, and the odds of those wagers. The user's interaction with the application may be recorded, along with their wagering data and a plurality of play characteristics. As the betting platform receives a new live play available to be wagered on, it may compare the characteristics of the new play to the user's history and may notify the user of the new play if it is highly correlated with their past wagering interactions with the platform.

Abstract: Quantification of a condition of a selected item using a neural network is disclosed. A device defines a good hypertube in a neural state space based on good item state points obtained from one or more items that exhibit desired operating characteristics, and a bad hypertube in the neural state space based on bad item state points obtained from one or more items that exhibit undesirable operating characteristics. A current item state hyperpoint is determined in the neural state space based on a current item state point of the selected item. A condition of the selected item is quantified as a function of a location of the current item state hyperpoint with respect to at least a portion of the good hypertube and with respect to at least a portion of the bad hypertube.

Abstract: Systems and methods are disclosed for more accurately estimating a remaining useful life (RUL) of an item. The RUL of the item is estimated by determining probability values throughout a time period. Each probability value quantifies a probability that a failure event of the item will occur by a time in a time segment of the time period. Based on the probability values, the particular time segment in which the failure event is most likely to occur is determined. Once the particular time segment is determined, the presentation of a visual representation of at least a portion of the time period can be effected. The visual representation indicates that the failure event of the item is most likely to occur during the particular time segment.

Abstract: Estimating a remaining useful life (RUL) of an apparatus is disclosed. A computer device may obtain a priori RUL data of an apparatus. The a priori RUL data identifies a priori RULs values of the apparatus as a function of time. Buckets are then defined in the a priori RUL data, wherein each of the buckets corresponds to a different set of the a priori RUL values in the a priori RUL data. An operational event indicator may then be obtained for the apparatus that indicates a current operational event of the apparatus. The RUL of an apparatus is estimated by determining probability values throughout a time period. Probability values are then determined based on the operational event indicator where each probability value quantifies a probability that a current RUL value of the first apparatus is within one of the buckets.

Abstract: Methods, apparatus, and computer-readable media for integrating two programming languages into a new programming language are disclosed. A plurality of programming statements are received, some of the plurality of programming statements having a first syntax representative of a first programming language and some of the plurality of programming statements having a second syntax representative of a second programming language. The some of the plurality of programming statements having the first syntax representative of the first programming language are translated into new programming statements in the second programming language. A source file is generated that comprises the some of the plurality of programming statements written in the second programming language and the new programming statements.

Abstract: Mechanisms for predicting a remaining useful life of a cutter head of a milling machine that includes a plurality of flutes are disclosed. Features are extracted from reference data associated with a plurality of reference cutter heads. The reference data includes reference vibration data and reference wear data. At least two Neural Network predictive models are trained in parallel for predicting the remaining life of a new cutter head based upon the extracted features. Operational data associated with the new cutter head is obtained. The operational data includes operational vibration data and operational wear data. Features extracted from the operational data are input into an optimal predictive model of the at least two Neural Network predictive models. A remaining useful life of the new cutter head is estimated by the optimal predictive model.

Abstract: Real-time condition-based analysis is performed on a machine for providing diagnostic and prognostic outputs indicative of machine status includes a signal processor for receiving signals from sensors adapted for measuring machine performance parameters. The signal processor conditions and shapes at least some of the received signals into an input form for a neural network. A fuzzy adaptive resonance theory neural network receives at least some of the conditioned and shaped signals, and detects and classifies a state of the machine based upon the received conditioned and shaped signals, and upon a predetermined ontology of machine states, diagnostics, and prognostics. The neural network can also determine from the machine state a health status thereof, which can comprise an anomaly, and output a signal representative of the determined health status. A Bayesian intelligence network receives the machine state from the neural network and determines a fault probability at a future time.

Abstract: Real-time condition-based analysis is performed on a machine for providing diagnostic and prognostic outputs indicative of machine status includes a signal processor for receiving signals from sensors adapted for measuring machine performance parameters. The signal processor conditions and shapes at least some of the received signals into an input form for a neural network. A fuzzy adaptive resonance theory neural network receives at least some of the conditioned and shaped signals, and detects and classifies a state of the machine based upon the received conditioned and shaped signals, and upon a predetermined ontology of machine states, diagnostics, and prognostics. The neural network can also determine from the machine state a health status thereof, which can comprise an anomaly, and output a signal representative of the determined health status. A Bayesian intelligence network receives the machine state from the neural network and determines a fault probability at a future time.

Abstract: The invention provides compounds of general formula (I) wherein Q, R, R2, R3, R4, R5, R6, R7, and R8 are as defined in the specification, processes for their preparation, pharmaceutical compositions containing them and their use in therapy.

Abstract: The invention provides compounds of general formula (I) wherein Q, R, R1, R4, R5, R6, R7 and R8 are as defined in the specification, processes for their preparation, pharmaceutical compositions containing them and their use in therapy.