Abstract: The invention relates to a method for training machine learning models, having the steps of: detecting data in the form of time series data using one or more computers, said data being obtained by means of one or more measuring devices (60-62), in each case in the form of a sensor for measuring a physical variable; receiving multiple classification data units relating to the data using the one or more computers; receiving a selected part of the data using the one or more computers for each of the classification data units; and training multiple machine learning models using the one or more computers, in each case on the basis of at least one of the classification data units and the at least one corresponding selected part of the data, wherein the multiple machine learning models represent multiple instances of the same machine learning model.

Abstract: An apparatus and method for provisioning virtualized tile-based graphics processing circuitry. For example, one embodiment of an apparatus comprises: processing resources to process commands including graphics commands and generate results; resource partitioning circuitry to partition the processing resources into a plurality of tiles in accordance with a specified tile-based resource allocation policy; and graphics virtualization circuitry to perform tile-based allocation of the processing resources to a plurality of virtual machines in accordance with a specified virtualization policy, the virtual machines to be executed in a virtualized execution environment.

Abstract: Provided is a method for calculating a timestamp associated with a data packet before transcoding of the data packet. The method may include sampling a time of day (TOD) signal to provide a sampled TOD. A previously sampled TOD estimate may be retrieved. An internal TOD estimate may be determined based on the sampled TOD and the previously sampled TOD estimate. A timestamp may be determined based on the internal TOD estimate. A system and computer program product are also disclosed.

Abstract: An electric-to-hydraulic conversion machine includes an axial flux electric motor and a hydraulic pump. The motor includes a spindle, at least one rotor configured to rotate about the spindle, and at least one stator configured to drive rotation of the at least one rotor about the spindle. The hydraulic pump includes a piston block having a plurality of cylinders, a plurality of pistons each supported in one of the cylinders of the piston block, and a cam ring. The piston block is attached to the at least one rotor and is configured to rotate about the spindle with rotation of the at least one rotor. The cam ring is configured to radially drive the pistons during rotation of the piston block about the spindle, which drives a fluid flow.

Abstract: A system includes a set of low resource devices, each configured to receive transactions to be added to an encrypted block chain ledger from a sample of untrusted high resource devices, prepare a proposed block of the received transactions, provide the proposed block to the sample of untrusted high resource devices, receive proposed blocks from the untrusted high resource devices originating from the set of low resource devices. The low resource devices run a consensus protocol to select one proposed block to add to the encrypted block chain ledger stored on the untrusted high resource devices.

Abstract: In one embodiment, a computer networking device calculates a first hash value for an identifier of a group of computing devices, as well as a second hash value for the identifier of the group of computing devices, with each hash value being at least in part on the identifier of the group of computing devices and an identifier of the respective interface. The computer networking device may also analyze the first hash value with respect to the second hash value and select the first interface for association with the identifier of the group of computing devices based at in part on the analyzing. The computer networking device may further store an indication that the identifier of the group of computing devices is associated with the first interface.

Abstract: Techniques are provided for predicting firmware installation failure reasons using machine learning techniques. One method comprises obtaining log data for a user device, wherein the log data is obtained following a failure of a firmware installation on the user device; extracting a plurality of features from the obtained log data; applying the extracted features to a trained machine learning model to obtain a prediction of whether the firmware installation failure is caused by a hardware-related failure or a software-related failure; and performing an automated remedial action based on a result of the prediction. The trained machine learning model can be trained using historical data for multiple user devices that experienced a firmware installation failure, where the historical data comprises a label indicating whether a given failure comprises a hardware-related failure or a software-related failure. The trained machine learning model can be trained and tested using cross-validation techniques.

Abstract: A sealing flange sector for a turbomachine rotor disc includes a radially outer part which is configured to bear at least partly against blades of the turbomachine rotor disc to ensure sealing between the blades and a radially inner part configured to bear on an annular strip mounted on a face of the turbomachine rotor disc, the radially inner part having a first groove disposed radially outwardly of a second groove. The first groove includes at least one foolproofing element.

Abstract: The present invention discloses a method, a system and a computer program product for Contract management. The invention includes optical character recognition for extraction of data attributes from the contracts. The invention further provides AI engine configured for processing a contract creation request through a bot based on analysis of a set of parameters associated with the request.

Abstract: Methods, systems and apparatuses may provide for technology that triggers an idle state in a first command streamer in response to a request to reset a second command streamer that shares graphics hardware with the first command streamer. The technology may also determine an event type associated with the request and conduct the request based on the event type.

Abstract: In one embodiment, a computer networking device calculates a first hash value for an identifier of a group of computing devices, as well as a second hash value for the identifier of the group of computing devices, with each hash value being at least in part on the identifier of the group of computing devices and an identifier of the respective interface. The computer networking device may also analyze the first hash value with respect to the second hash value and select the first interface for association with the identifier of the group of computing devices based at in part on the analyzing. The computer networking device may further store an indication that the identifier of the group of computing devices is associated with the first interface.

Abstract: Implementations described herein relate to methods, systems, and computer-readable media to personalize recommendations. In some implementations, a method includes computing a user-based similarity matrix and a game-based similarity matrix, obtaining a set of user scores from a first machine learning model and the user-based similarity matrix, and obtaining a set of game scores from a second machine learning model and the game-based similarity matrix. The method also includes combining the set of user scores and the set of game scores to generate a normalized set of scores, identifying a set of personalized recommendations for the user associated with a subset of the normalized set of scores, assigning a rank to each of the plurality of items, generating a list of items wherein items in the list of items are ordered based on respective ranks, and providing a user interface to the user that includes the list of items.

Abstract: The present invention is directed to novel crystalline forms of 5-(4-{[2-fluorophenyl)methyl]oxy}phenyl-prolinamide hydrochloride, to the use of said crystalline forms in treating diseases and conditions mediated by modulation of voltage-gated sodium channels, to compositions containing said crystalline forms and processes for their preparation.

Abstract: Methods and apparatuses for performing atomic layer deposition are provided. A method may include determining an amount of accumulated deposition material currently on an interior region of a deposition chamber interior, wherein the amount of accumulated deposition material changes over the course of processing a batch of substrates; applying the determined amount of accumulated deposition material to a relationship between a number of ALD cycles required to achieve a target deposition thickness, and a variable representing an amount of accumulated deposition material, wherein the applying returns a compensated number of ALD cycles for producing the target deposition thickness given the amount of accumulated deposition material currently on the interior region of the deposition chamber interior; and performing the compensated number of ALD cycles on one or more substrates in the batch.

Abstract: Provided is a method for calculating a timestamp associated with a data packet before transcoding of the data packet. The method may include sampling a time of day (TOD) signal to provide a sampled TOD. A previously sampled TOD estimate may be retrieved. An internal TOD estimate may be determined based on the sampled TOD and the previously sampled TOD estimate. A timestamp may be determined based on the internal TOD estimate. A system and computer program product are also disclosed.

Abstract: Certain aspects of the present disclosure provide techniques for generalized metric for machine learning model evaluation for unsupervised classification including: for each unsupervised machine learning model of one or more unsupervised machine learning models: generating a first set of synthetic inputs for the model of the one or more unsupervised machine learning models; providing the first set of synthetic inputs to the model trained to output a prediction for each input of the first set of synthetic inputs, wherein the prediction indicates whether the input is of a first class; identifying, based on an output of the model, a second set of synthetic inputs predicted to be of the first class; determining, based on a set of expected normal inputs for the model and the second set of synthetic inputs, an accuracy score for the unsupervised machine learning model; and providing the accuracy score for display.

Abstract: A mechanism is disclosed for automatically detecting whether the client device is experiencing wireless communication issues and switching communications from a first server group to second server group, if necessary. Responsive to determining that the client device is experiencing wireless communication issues, the system performs a health check against the second server group, and responsive to determining, based on the health check, that the issue is on the client device, the system refrains from failing over to the second server group. Responsive to determining that the client device is not experiencing issues, the system fails over to a second server group. When the client device determines that the first server group is available, the client device fails back to the first server group.

Abstract: The invention discloses methods for simultaneously measuring various properties of a fluid using a waveguide. The method includes transmitting a plurality of wave modes into the fluid using an ultrasonic shear wave transducer from one end of a waveguide. Further, the wave modes are reflected from the other end of the waveguide. The reflected wave modes are processed simultaneously. The time of flight and the amplitude of the received wave modes are determined. Further, one or more properties of the fluid are measured using determined time of flight and amplitude of the received wave modes. The disclosed method is used to accurately measure the properties of fluid such as level, density, viscosity or flow rate in a short period of time.

Abstract: An apparatus and method for provisioning virtualized tile-based graphics processing circuitry. For example, one embodiment of an apparatus comprises: processing resources to process commands including graphics commands and generate results; resource partitioning circuitry to partition the processing resources into a plurality of tiles in accordance with a specified tile-based resource allocation policy; and graphics virtualization circuitry to perform tile-based allocation of the processing resources to a plurality of virtual machines in accordance with a specified virtualization policy, the virtual machines to be executed in a virtualized execution environment.