Abstract: The present disclosure generally relates to a primary load management system configured to execute machine learning and artificial intelligence techniques to generate predictions of access-right requests that are or are likely to be invalid before the access-right requests are processed for assignment to users or user devices. The present disclosure relates to systems and methods that collect a data set representing characteristics of user devices as the user devices interact with various systems of the primary load management system and train a machine-learning model to predict invalid access-right requests using the collected data set. The collected data set may include a log line that represents each user device, and each log line may be labeled based on an invalidity evaluation. New access-right requests can be processed using the trained machine-learning model to determine whether or not to assign access rights in response to the access-right request.

Abstract: Certain embodiments of the present disclosure relate to systems and methods that control access to system resources, such as interfaces, access rights to events, query systems, and other suitable system resources. Further, certain embodiments of the present disclosure relate to a collision detection technique that is implemented to control which and/or a number of queue positions within a queue that are processed. In some implementations, a collision may be detected when two or more users request the same access right within a defined time period.

Abstract: Systems and methods may use models to generate predictions of specific access rights for users. Further, systems and methods may generate the predictions in an environment in which the availability of the specific access rights change frequently. The access rights, predicted using embodiments described herein, may be both available and associated with user affinities. An interface associated with the primary load management system may be configured to display the predicted access rights for a user operating a user device.

Abstract: Certain embodiments of the present disclosure relate to systems and methods that control access to system resources, such as interfaces, access rights to events, query systems, and other suitable system resources. Further, certain embodiments of the present disclosure relate to a collision detection technique that is implemented to control which and/or a number of queue positions within a queue that are processed. In some implementations, a collision may be detected when two or more users request the same access right within a defined time period.

Abstract: Systems and methods may use models to generate predictions of specific access rights for users. Further, systems and methods may generate the predictions in an environment in which the availability of the specific access rights change frequently. The access rights, predicted using embodiments described herein, may be both available and associated with user affinities. An interface associated with the primary load management system may be configured to display the predicted access rights for a user operating a user device.

Abstract: Certain embodiments of the present disclosure relate to systems and methods that control access to system resources, such as interfaces, access rights to events, query systems, and other suitable system resources. Further, certain embodiments of the present disclosure relate to a collision detection technique that is implemented to control which and/or a number of queue positions within a queue that are processed. In some implementations, a collision may be detected when two or more users request the same access right within a defined time period.

Abstract: Systems and methods may use models to generate predictions of specific access rights for users. Further, systems and methods may generate the predictions in an environment in which the availability of the specific access rights change frequently. The access rights, predicted using embodiments described herein, may be both available and associated with user affinities. An interface associated with the primary load management system may be configured to display the predicted access rights for a user operating a user device.

Abstract: The present disclosure generally relates to a primary load management system configured to execute machine learning and artificial intelligence techniques to generate predictions of access-right requests that are or are likely to be invalid before the access-right requests are processed for assignment to users or user devices. More particularly, the present disclosure relates to systems and methods that collect a data set representing characteristics of user devices as the user devices interact with various systems of the primary load management system, train a machine-learning model to predict invalid access-right requests using the collected data set, and execute the trained machine-learning model to process new access-right requests to generate predictions as to whether or not the new access-right requests are invalid.

Abstract: Certain embodiments of the present disclosure relate to systems and methods that control access to system resources, such as interfaces, access rights to events, query systems, and other suitable system resources. Further, certain embodiments of the present disclosure relate to a collision detection technique that is implemented to control which and/or a number of queue positions within a queue that are processed. In some implementations, a collision may be detected when two or more users request the same access right within a defined time period.

Abstract: Systems and methods may use models to generate predictions of specific access rights for users. Further, systems and methods may generate the predictions in an environment in which the availability of the specific access rights change frequently. The access rights, predicted using embodiments described herein, may be both available and associated with user affinities. An interface associated with the primary load management system may be configured to display the predicted access rights for a user operating a user device.

Abstract: The present disclosure generally relates to a primary load management system configured to execute machine learning and artificial intelligence techniques to generate predictions of access-right requests that are or are likely to be invalid before the access-right requests are processed for assignment to users or user devices. The present disclosure relates to systems and methods that collect a data set representing characteristics of user devices as the user devices interact with various systems of the primary load management system and train a machine-learning model to predict invalid access-right requests using the collected data set. The collected data set may include a log line that represents each user device, and each log line may be labeled based on an invalidity evaluation. New access-right requests can be processed using the trained machine-learning model to determine whether or not to assign access rights in response to the access-right request.

Abstract: Certain embodiments of the present disclosure relate to systems and methods that control access to system resources, such as interfaces, access rights to events, query systems, and other suitable system resources. Further, certain embodiments of the present disclosure relate to a collision detection technique that is implemented to control which and/or a number of queue positions within a queue that are processed. In some implementations, a collision may be detected when two or more users request the same access right within a defined time period.

Abstract: Systems and methods may use models to generate predictions of specific access rights for users. Further, systems and methods may generate the predictions in an environment in which the availability of the specific access rights change frequently. The access rights, predicted using embodiments described herein, may be both available and associated with user affinities. An interface associated with the primary load management system may be configured to display the predicted access rights for a user operating a user device.

Abstract: Certain embodiments of the present disclosure relate to systems and methods that control access to system resources, such as interfaces, access rights to events, query systems, and other suitable system resources. Further, certain embodiments of the present disclosure relate to a collision detection technique that is implemented to control which and/or a number of queue positions within a queue that are processed. In some implementations, a collision may be detected when two or more users request the same access right within a defined time period.

Abstract: Systems and methods may use models to generate predictions of specific access rights for users. Further, systems and methods may generate the predictions in an environment in which the availability of the specific access rights change frequently. The access rights, predicted using embodiments described herein, may be both available and associated with user affinities. An interface associated with the primary load management system may be configured to display the predicted access rights for a user operating a user device.

Abstract: Systems and methods may use models to generate predictions of specific access rights for users. Further, systems and methods may generate the predictions in an environment in which the availability of the specific access rights change frequently. The access rights, predicted using embodiments described herein, may be both available and associated with user affinities. An interface associated with the primary load management system may be configured to display the predicted access rights for a user operating a user device.

Abstract: A system for selecting a video to be inserted into an article displayed at a web page includes a blackboard. The blackboard stores extracted values for operation thereon by one or more workers. An article extractor creates an article feature as a function of information extracted from the article and inputs the article feature to the blackboard. A threshold extractor determines a threshold factor as a function of the relevance of the video to the article, and inputting the threshold factor to the blackboard. A more like this recommender receives the article feature and outputs to the blackboard, as a function of the article feature, a more like this recommendation as a list of videos to be placed in the article. A more like this decider determines, as a function of the threshold factor and the more like this recommendation, which video to select as a more like this decision.

Abstract: Cable end section comprises end-parts of N electrical phases/neutral, and a thermally-insulation envelope comprising cooling fluid. The end-parts each comprises a conductor and are arranged with phase 1 innermost, N outermost surrounded by the neutral, electrical insulation being between phases and N and neutral. The end-parts comprise contacting surfaces located sequentially along the longitudinal extension of the end-section. A termination unit has an insulating envelope connected to a cryostat, special parts at both ends comprising an adapter piece at the cable interface and a closing end-piece terminating the envelope in the end-section. The special parts houses an inlet and/or outlet for cooling fluid. The space between an inner wall of the envelope and a central opening of the cable is filled with cooling fluid. The special part at the end connecting to the cryostat houses an inlet or outlet, splitting cooling flow into cable annular flow and termination annular flow.

Abstract: Cable end section comprises end-parts of N electrical phases/neutral, and a thermally-insulation envelope comprising cooling fluid. The end-parts each comprises a conductor and are arranged with phase 1 innermost, N outermost surrounded by the neutral, electrical insulation being between phases and N and neutral. The end-parts comprise contacting surfaces located sequentially along the longitudinal extension of the end-section. A termination unit has an insulating envelope connected to a cryostat, special parts at both ends comprising an adapter piece at the cable interface and a closing end-piece terminating the envelope in the end-section. The special parts houses an inlet and/or outlet for cooling fluid. The space between an inner wall of the envelope and a central opening of the cable is filled with cooling fluid. The special part at the end connecting to the cryostat houses an inlet or outlet, splitting cooling flow into cable annular flow and termination annular flow.

Abstract: The invention relates to a superconductive multi-phase, fluid-cooled cable system comprising a) a cable comprising at least three electrical conductors constituting at least two electrical phases and a zero- or neutral conductor, said electrical conductors being mutually electrically insulated from each other, and b) a thermal insulation defining a central longitudinal axis and having an inner surface and surrounding the cable, said inner surface of said thermal insulation forming the radial limitation of a cooling chamber for holding a cooling fluid for cooling said electrical conductors. The invention further relates to a method of manufacturing a cable system and to its use. The object of the present invention is to provide a simplified manufacturing and installation scheme for a fluid cooled cable system.