Abstract: Described herein are systems and methods for real-time integration of resources across disparate electronic platforms, including automated data mapping and message translation for improved resource platform access. The embodiments provide technical solutions and technical improvements that overcome technical problems, drawbacks and/or deficiencies in the technical fields involving compatibility with multiple third-party APIs, unified access to data from multiple platforms, and efficient synchronization with multiple platforms. Technical solutions and technical improvements herein include aspects of improved API call normalization for scalable and flexible API calls that integrate with various platforms, proactive and/or real-time caching of data associated with the various platforms, and efficient orchestration of client queries, platform API calls and cache querying to answer the client queries most efficiently and quickly with up-to-date, synchronized data.

Abstract: A source of a login attempt to a user account can be classified using machine learning. For example, a computing system can input user activity observations associated with one or more login attempts to one or more user accounts into a trained machine learning model. One or more distinguishing factors for the one or more login attempts can be received from the trained machine learning model. The computing system can determine a source of a current login attempt by applying a clustering algorithm to current values of the one or more distinguishing factors. The current values may be derived from current user activity observations associated with the current login attempt. The computing system can determine an authentication level for the current login attempt to the user account based on the source of the current login attempt.

Abstract: A medical apparatus has a thrombectomy device disposed in a sheath lumen of a sheath that is movable between an initial extended position and a retracted position. The thrombectomy device includes a first elongate cannula having a distal tip, a guidewire lumen, and a perforated region, which is proximal to the distal tip and is in fluid communication with the guidewire lumen. A second elongate cannula, which is configured to rotate, has a second lumen and a mechanical thrombectomy whisk, which is proximal to the distal tip. A third elongate cannula has a third exterior surface, a third lumen, an inflation passageway, an inflatable balloon connected to the third exterior surface, and an expandable embolic filter connected to the third exterior surface at a location distal to the inflatable balloon. The first elongate cannula is disposed in the second lumen. The second elongate cannula is disposed in the third lumen.

Abstract: According to an embodiment of the present invention, an automated computer implemented method and system for providing targeted content in real-time comprises a web and application server that identifies one or more user interactions from a user on a website hosted by an entity; a processor that receives the one or more user interactions and converts the one or more user interactions into one or more real-time attributes; and an engine that identifies customized content for the user from a remote processor, adjusts the customized content based on the one or more real-time attributes, and generates an output comprising the customized content for display on the website for the user in real-time.

Abstract: In an example embodiment, a solution is provided wherein a threshold used by a classifier in a first machine learning model is dynamically set by a second machine learning model. More particularly, the threshold may be selected from two or more different threshold settings, based on the output of the second machine learning model. This acts to improve the reliability of predictions made by the first machine learning model in certain use cases where circumstances not adequately captured by the first machine learning model can affect the accuracy of the threshold used by the first machine learning model.

Abstract: Described herein are systems and methods for real-time automated data indexing of resources across disparate electronic platforms, including automated data mapping and message translation for improved resource platform access. A cache may refresh (e.g., on a periodic basis) resource objects regarding resources and resource availability from each resource platform. The resources may include providers, and the information can include name/identifier, capabilities, type, availability, etc. unstructured responses obtained from calls to refresh the objects may be parsed and reformatted into a common format using platform-specific configurations, and then stored in a resource cache such that subsequent users can request the resource that is secured by interacting with the resource cache instead of the resource platform.

Abstract: A source of a login attempt to a user account can be classified using machine learning. For example, a computing system can input user activity observations associated with one or more login attempts to one or more user accounts into a trained machine learning model. One or more distinguishing factors for the one or more login attempts can be received from the trained machine learning model. The computing system can determine a source of a current login attempt by applying a clustering algorithm to current values of the one or more distinguishing factors. The current values may be derived from current user activity observations associated with the current login attempt. The computing system can determine an authentication level for the current login attempt to the user account based on the source of the current login attempt.

Abstract: Described herein are systems and methods for real-time integration of resources across disparate electronic platforms, including automated data mapping and message translation for improved resource platform access. The embodiments provide technical solutions and technical improvements that overcome technical problems, drawbacks and/or deficiencies in the technical fields involving compatibility with multiple third-party APIs, unified access to data from multiple platforms, and efficient synchronization with multiple platforms. Technical solutions and technical improvements herein include aspects of improved API call normalization for scalable and flexible API calls that integrate with various platforms, proactive and/or real-time caching of data associated with the various platforms, and efficient orchestration of client queries, platform API calls and cache querying to answer the client queries most efficiently and quickly with up-to-date, synchronized data.

Abstract: Described herein are systems and methods for real-time automated data indexing of resources across disparate electronic platforms, including automated data mapping and message translation for improved resource platform access. A cache may refresh (e.g., on a periodic basis) resource objects regarding resources and resource availability from each resource platform. The resources may include providers, and the information can include name/identifier, capabilities, type, availability, etc. unstructured responses obtained from calls to refresh the objects may be parsed and reformatted into a common format using platform-specific configurations, and then stored in a resource cache such that subsequent users can request the resource that is secured by interacting with the resource cache instead of the resource platform.

Abstract: A source of a login attempt to a user account can be classified using machine learning. For example, a computing system can input user activity observations associated with one or more login attempts to one or more user accounts into a trained machine learning model. One or more distinguishing factors for the one or more login attempts can be received from the trained machine learning model. The computing system can determine a source of a current login attempt by applying a clustering algorithm to current values of the one or more distinguishing factors. The current values may be derived from current user activity observations associated with the current login attempt. The computing system can determine an authentication level for the current login attempt to the user account based on the source of the current login attempt.

Abstract: Described herein are systems and methods for real-time integration of resources across disparate electronic platforms, including automated data mapping and message translation for improved resource platform access. The embodiments provide technical solutions and technical improvements that overcome technical problems, drawbacks and/or deficiencies in the technical fields involving compatibility with multiple third-party APIs, unified access to data from multiple platforms, and efficient synchronization with multiple platforms. Technical solutions and technical improvements herein include aspects of improved API call normalization for scalable and flexible API calls that integrate with various platforms, proactive and/or real-time caching of data associated with the various platforms, and efficient orchestration of client queries, platform API calls and cache querying to answer the client queries most efficiently and quickly with up-to-date, synchronized data.

Abstract: Described herein are systems and methods for real-time automated data indexing of resources across disparate electronic platforms, including automated data mapping and message translation for improved resource platform access. A cache may refresh (e.g., on a periodic basis) resource objects regarding resources and resource availability from each resource platform. The resources may include providers, and the information can include name/identifier, capabilities, type, availability, etc. unstructured responses obtained from calls to refresh the objects may be parsed and reformatted into a common format using platform-specific configurations, and then stored in a resource cache such that subsequent users can request the resource that is secured by interacting with the resource cache instead of the resource platform.

Abstract: A source of a login attempt to a user account can be classified using machine learning. For example, a computing system can input user activity observations associated with one or more login attempts to one or more user accounts into a trained machine learning model. One or more distinguishing factors for the one or more login attempts can be received from the trained machine learning model. The computing system can determine a source of a current login attempt by applying a clustering algorithm to current values of the one or more distinguishing factors. The current values may be derived from current user activity observations associated with the current login attempt. The computing system can determine an authentication level for the current login attempt to the user account based on the source of the current login attempt.

Abstract: In an example embodiment, a solution is provided wherein a threshold used by a classifier in a first machine learning model is dynamically set by a second machine learning model. More particularly, the threshold may be selected from two or more different threshold settings, based on the output of the second machine learning model. This acts to improve the reliability of predictions made by the first machine learning model in certain use cases where circumstances not adequately captured by the first machine learning model can affect the accuracy of the threshold used by the first machine learning model.

Abstract: Described herein is a food holder including a multiple-panel sleeve that may include a front panel, a rear panel, two front-side panels and two back-side panels that form an irregular shape. The multiple-panel sleeve includes a bottom member connected to bottom edges of the front and rear panels. The irregular, tapered shape of the bottom member promotes the structural integrity of the food holder.

Abstract: A cluster of nodes, comprising: a plurality of nodes, each having a security policy, and being associated task processing resources; a registration agent configured to register a node and issue a node certificate to the respective node; a communication network configured to communicate certificates to authorize access to computing resources, in accordance with the respective security policy; and a processor configured to automatically dynamically partition the plurality of nodes into subnets, based on at least a distance function of at least one node characteristic, each subnet designating a communication node for communicating control information and task data with other communication nodes, and to communicate control information between each node within the subnet and the communication node of the other subnets.

Abstract: A cluster of nodes, comprising: a plurality of nodes, each having a security policy, and being associated task processing resources; a registration agent configured to register a node and issue a node certificate to the respective node; a communication network configured to communicate certificates to authorize access to computing resources, in accordance with the respective security policy; and a processor configured to automatically dynamically partition the plurality of nodes into subnets, based on at least a distance function of at least one node characteristic, each subnet designating a communication node for communicating control information and task data with other communication nodes, and to communicate control information between each node within the subnet and the communication node of the other subnets.