Abstract: A method and a system for automatically generating one or more real time updates for at least one live event is described. In one example, a processing unit is connected to a storage unit and a display unit, said processing unit fetches a content stream of the at least one live event and identifies at least one moment from the content stream. Based on the identified moment, at least one real time update is generated by the processing unit. The generated real time updated is then displayed on the display unit.

Abstract: A reference assembly connected to a support ring of an external fixation frame. The reference assembly includes a mount device. The mount device includes a mount body, a static member, and a dynamic member. The static member is fixedly secured to and extends from the mount body and is configured to be received within a first hole of the support ring of the external fixation frame. The dynamic member is slidably connected to the mount body and is configured to be received within a second hole of the support ring. The reference assembly also includes a reference device that is connectable to the mount body. The reference device includes reference body and a plurality of reference objects disposed within the reference body. The reference objects are each made from a radiopaque material, and the reference body is made from a radiolucent material.

Abstract: Methods and systems are described for audio pipelines between a user and a machine learning (ML) model. The method involves obtaining digital audio data associated with an audio signal from a user's equipment. This data is then analyzed using a trained ML model, which includes one or more neural networks. The ML model determines an indication related to the digital audio data, which can be a prediction of the ending of one or more portions of the data, an intention behind the data, a key term within the data, an action to take based on the data, or the context associated with the data. Based on the determined indication, a response is generated and subsequently transmitted back to the user's equipment.

Abstract: Quantum-based vulnerability and risk identification systems and processes are disclosed that identify vulnerabilities in configuration items (CIs) before changes are deployed. A contrastive learning algorithm compares vectors of CIs to vectors of known vulnerable components and further refines the most relevant features from those filters. Federated Learning enhances model performance, and a quantum optimization system (QOS) optimizes the results generated by the contrastive model as it has an advantage of solving optimization problems formulated with distinct variables. Proactive prediction mechanism is provided through contrastive learning. QOS provides enhanced vulnerability detection system and change management lifecycle. QOS provides deterministic results by finding optimized solutions in high-dimensional solution spaces.

Abstract: The present disclosure provides system (102) and method (300) for enabling speed test of internet connection using a mobile application. The mobile application selects an appropriate server and initiates the data transfer by sending and receiving packets of data to and from the server. The data size and duration of the test can vary, but larger sample sizes generally provide more accurate results therefore multiple threads with increasing buffer size are used during the test time. The system measures the time it takes for the data transfer to complete in both the upload and download directions. The timing is crucial for determining the speeds. A speed test empowers users with the ability to measure, evaluate, and understand the performance of the internet connection. Thus, enabling the users to make informed decisions and ensure they receive reliable and satisfactory internet service.

Abstract: Using a machine learning model query on received content, one or more statements in the content that meet one or more candidate criteria for correctness verification are automatically identified. For at least one statement of the identified one or more statements, a machine learning model is used to assess correctness of the at least one statement including by searching resources associated with the at least one statement to determine a search result and evaluating the search result. A revision of at least one statement assessed to be incorrect in the identified one or more statements is automatically determined. In some embodiments, a bias report is generated, wherein the bias report compares two or more resources identified by the search result and used to assess the correctness of the at least one statement.

Abstract: A system and method of operating a vehicle. The system includes an inverter, a motor, and a sensor for measuring a phase current between the inverter and the motor in a first phase cycle in which the inverter is operated at a first voltage. A processor predicts an observed phase current and a raw disturbance voltage for the second phase cycle from the phase current, calculates a damping voltage correction for the second phase cycle from the observed phase current and a disturbance voltage correction for the second phase cycle from the raw disturbance voltage, calculates a final voltage in the second phase cycle from a core current regulator voltage, the damping voltage correction and the disturbance voltage correction, calculates a second voltage in the first phase cycle by applying a delay to the final voltage in the second phase cycle; and applies the second voltage at the inverter.

Abstract: Disclosed are various embodiments for self-healing data clusters. One or more candidates are determined from the candidate pool to be evaluated with the new record. A unique pair combination is generated for each one of the candidates of the candidate pool and the new record. Next, candidate data for the one or more candidates is identified from the existing record based at least in part on one or more matching rules. A weight is assigned to one or more matching rules. Then, the candidate data of the one or more candidates and the new record is evaluated for a data linkage. A distance is calculated between each of the unique pair combinations. Finally, the candidates of the existing record and the new record are clustered into groups.

Abstract: Aspects of the disclosure relate to s computing system that is configured to use heuristic and/or metaheuristic algorithms based on swarm learning (SL) intelligence frameworks and combine SL with blockchain and edge computing frameworks to provide a technologically efficient, responsive, and/or adaptable solution to detecting and preventing defects in software applications.

Abstract: Aspects of the disclosure relate to s computing system that is configured to use heuristic and/or metaheuristic algorithms based on swarm learning (SL) intelligence frameworks and combine SL with blockchain and edge computing frameworks to provide a technologically efficient, responsive, and/or adaptable solution to detecting and preventing defects in software applications.

Abstract: Aspects of the disclosure relate to s computing system that is configured to use heuristic and/or metaheuristic algorithms based on swarm learning (SL) intelligence frameworks and combine SL with blockchain and edge computing frameworks to provide a technologically efficient, responsive, and/or adaptable solution to detecting and preventing defects in software applications.

Abstract: Devices, systems, and methods are provided for user profile management across multiple devices. A method may include determining, by a first device, that the first device is signed into a customer account; determining that the customer account includes a first user profile and a second user profile, the first user profile having first identity data, and the second user profile having second identity data; determining that third identity data for the first user profile is available for presentation, the third identity data based on a user interaction with a second device; determining that the first user profile is enrolled on the first device; presenting the first identity data using the first device; receiving a second user request to access the first user profile; and presenting, using the first device, content based on the second user request and a user preference associated with the first user profile.

Abstract: The present invention is directed to substituted certain 1-pyrazolyl, 5-, 6-disubstituted indazole derivatives of Formula (I) and pharmaceutically acceptable salts thereof, wherein R1, R2, and ring A are as defined herein, which are potent inhibitors of LRRK2 kinase and may be useful in the treatment or prevention of diseases in which the LRRK2 kinase is involved, such as Parkinson's Disease and other diseases and disorders described herein. The invention is also directed to pharmaceutical compositions comprising these compounds and the use of these compounds and compositions in the prevention or treatment of diseases, such as Parkinson's disease, in which LRRK-2 kinase is involved.

Abstract: The techniques and circuits, described herein, include solutions for compensating for integrator drift. A drift compensation circuit has a first terminal coupled to an output of an integrator, and a second terminal coupled to an input of the integrator. The drift compensation circuit is configured to sense integrator drift at the output of the integrator, and provide a compensation signal to the input of the integrator based on the sensed drift. The input of the integrator may be coupled to an output of an additional integrator. By sensing the integrator drift at the end of the signal chain, and providing the compensation signal earlier in the signal chain, the compensation signal can compensate for integrator drift from multiple integrators in the system.

Abstract: The present disclosure relates to a system and a method for stream distribution. The method includes: determining a first parameter of a distributor to be higher or lower than a first threshold; determining a first viewer to have a second parameter higher than a second threshold with respect to streams recommended to the first viewer; determining a second viewer to have a second parameter lower than the second threshold with respect to streams recommended to the second viewer; and recommending a stream of the distributor to the first viewer or the second viewer according to a result of the determining the first parameter to be higher or lower than the first threshold.

Abstract: An eccentricity detection system includes: a vibration eccentricity module configured to determine a vibration eccentricity of the electric motor based on vibration of the electric motor measured during operation of the motor; an inductance eccentricity module configured to determine an inductance eccentricity of the electric motor based on an incremental inductance curve of the electric motor; and a fault module configured to indicate whether the electric motor includes an eccentricity fault based on both (a) the vibration eccentricity of the electric motor and (b) the inductance eccentricity of the electric motor.

Abstract: A system including one or more processors is provided. The one or more processors can receive data regarding charging sessions of electric vehicles at a plurality of chargers. The one or more processors can generate a score for each of the plurality of chargers based at least on the data regarding the charging sessions. The one or more processors can generate a path from a current location of a vehicle to a destination that includes a location for each of at least one of the plurality of chargers selected at least based on the scores. The one or more processors can update a user interface to depict the path including the location for each of the at least one of the plurality of chargers.

Abstract: A plethysmograph variability processor inputs a plethysmograph waveform having pulses corresponding to pulsatile blood flow within a tissue site. The processor derives plethysmograph values based upon selected plethysmograph features, determines variability values, and calculates a plethysmograph variability parameter. The variability values indicate the variability of the plethysmograph features. The plethysmograph variability parameter is representative of the variability values and provides a useful indication of various physiological conditions and the efficacy of treatment for those conditions.

Abstract: Various systems, methods, and devices are described for AI platform that may utilize a machine learning model configured to generate one or more overlays associated with a received input. In an example, systems and methods of generating one or more overlays may include receiving a media item and an input. The input may be natural language text or audio associated with a user. The machine learning model may be used to determine context associated with the input. Based on determining the context of the input, the machine learning model may generate one or more overlays. The user may select from the one or more overlays, indicating one or more overlays to user in conjunction to the media item. A combined media may be provided to the user where the selected overlays may be superimposed on the media item.

Abstract: A computer-implemented method includes receiving information corresponding to a data center, the information including an identifier of a type of the data center, identifying a server cluster type according to the data center type, outputting, to a user interface, a predefined list configured to obtain mapping information from a user, wherein the predefined list and mapping information are structured based on the server cluster type, receiving the mapping information from the user interface in response to the predefined list, wherein the mapping information includes one or more identifiers of material installed in the data center, and storing the structured mapping information in a storage device.