Abstract: Descriptors of machine learning tasks to be used to respond to analysis requests, indicating acceptable categories of runtime environments for the tasks and metrics to be collected from the tasks, are received via programmatic interfaces. In response to an analysis request, an orchestrator receives results from individual tasks as they become available, provides the results to other tasks, and causes a response to the request to be prepared using results from at least a subset of the tasks. Metrics collected from the tasks, and a visual representation of the tasks indicating their runtime environments are presented.

Abstract: One disclosed method involves accessing, by a computing system and using access credentials associated with a user, data associated with systems of record, generating, by the computing system, a plurality of notifications of events indicated by the data, determining, by the computing system, that the user selected at least one keyword, determining, by the computing system, that a first notification of the plurality of notifications relates to the at least one keyword, and causing, by the computing system and based at least in part on the first notification relating to the at least one keyword, a client device operated by the user to present the first notification.

Abstract: According to one embodiment, a data processing apparatus includes a processor provided with hardware. The processor extracts a first event data item, a second event data item, and a third event data item from input first document data. When a first relational data item indicating a presence of transitivity between the first event data item and the second event data item is extracted and a second relational data item indicating a presence of transitivity between the second event data item and the third event data item is extracted, the processor generates a third relational data item indicating a presence of a relation between the first event data item and the third event data item.

Abstract: A host upgrade method and a device include selecting at least one target host from a plurality of hosts for an upgrade. After the at least one target host is selected, a service running on all virtual machines that are in one or more target service groups and that are deployed on the at least one target host is stopped, and a service running on a virtual machine that is in the one or more target service groups and that is not deployed on the at least one target host is maintained. Then, the at least one target host is upgraded.

Abstract: A test application programming interface (API) request may be issued to a test service implementation. A test API response, which is responsive to the test API request, may be received from the test service implementation. First contents of the test API response may be compared to second contents of a control API response. The comparing may be performed based at least in part on a set of one or more expected differences associated with the test API response and the control API response. It may be determined, based on the comparing, whether an unexpected difference exists between the test API response and the control API response. An indication may be provided of whether the unexpected difference exists between the test API response and the control API response, and the unexpected difference may be automatically corrected, such as via one or more configuration changes.

Abstract: Cached data is obtained from a device. The cached data includes data saved on the device in response to electronic searches or electronic messaging performed by a user using the device. A determination is made, at least in part via the cached data, regarding an intended use context associated with the electronic searches or the electronic messaging. Using the intended use context, a confidence level is determined. In response to the determined confidence level meeting or exceeding a predefined threshold, a transaction involving the user is automatically executed, or an electronic communication is automatically sent on behalf of the user.

Abstract: A system comprising: at least one hardware processor; and a non-transitory computer-readable storage medium having stored thereon program instructions, the program instructions executable by the at least one hardware processor to: receive a data stream representing events; receive a plurality of complex event patterns (CEPs) comprising (a) a set of conditions reflecting relations among said events, and (b) a set of attributes associated with each of said events; and calculate an optimal multi-pattern evaluation plan corresponding to said CEPs by: (i) generating an initial evaluation plan, (ii) applying a search method to calculate modified versions of said initial evaluation plan, (iii) assigning a score to each of said modified versions based on a cost function, and (iv) selecting one of said modified versions having a highest said score as said optimal multi-pattern evaluation plan.

Abstract: An event processing method of a processor according to one or more embodiments may include detecting an event input, which notifies an occurrence of an event, detecting a wait event by an event input, changing a status from an execution status to a wait status and outputs a count start signal by an event wait instruction, and changes a status from the wait status to the execution status and outputs a count end signal by the detection of the wait event, incrementing a counter value from an initial value by output of the count start signal, and ends counting by output of the count end signal; and receiving and storing a count value of the timer counter by output of the count end signal.

Abstract: The technology disclosed relates to simplifying updating of a predictive model using clustering observed points. In particular, it relates to observing a set of points in 3D sensory space, determining surface normal directions from the points, clustering the points by their surface normal directions and adjacency, accessing a predictive model of a hand, refining positions of segments of the predictive model, matching the clusters of the points to the segments, and using the matched clusters to refine the positions of the matched segments. It also relates to distinguishing between alternative motions between two observed locations of a control object in a 3D sensory space by accessing first and second positions of a segment of a predictive model of a control object such that motion between the first position and the second position was at least partially occluded from observation in a 3D sensory space.

Abstract: A service may be provided that reads sensors, and that communicates information based on the sensor readings to applications. In one example, an operating system provides a sensor interface that allows programs that run on a machine to read the values of sensors (such as an accelerometer, light meter, etc.). A service may use the interface to read the value of sensors, and may receive subscriptions to sensor values from other programs. The service may then generate messages that contain the sensor value, and may provide these messages to programs that have subscribed to the messages. The messages may contain raw sensor data. Or, the messages may contain information that is derived from the sensor data and/or from other data.

Abstract: A system receives a request to process data. The system uses an expression engine to apply one or more expressions to the data to perform one or more application programming interface (API) interactions, which may include one or more of: dynamic resolution of API endpoints, API payload construction, and validation of API payload data fields. The Expressions are predefined entities configured to perform actions involving the system. The system initiates the expression engine. The system executes an initial expression upon initial data to produce an expression result. Executing the initial expression can involve iteratively resolving an ordered set of related expressions.

Abstract: In variants, the system can include a set of blockchain modules and a set of interaction mechanism handlers configured to convert a unified set of system commands into blockchain-specific commands for each of a set of blockchains and/or blockchain nodes.

Abstract: Disclosed information handling systems and methods employ a background module running in an operating system of a client platform to evaluate, after defined context-relevant events including, as examples, reboot, application launch, return from sleep/idle mode, change of network connection, and change of device, the impact of the user context change, and to take or recommend appropriate action. Embodied solutions may augment existing communication protocols, such as the Server Message Block (SMB) protocol, that enable and support shared access to files across nodes of a distributed system.

Abstract: Systems, methods, and software disclosed herein relate to a common gateway platform system. In an implementation, program instructions direct a computing system to execute a common gateway platform environment comprising an adapter comprising an adapter name identification, a broker connected to the adapter, and an application connected to the adapter. The application also generates an action configured according to a common gateway platform protocol, transmit the action to the broker, and receive a reaction from the broker. The broker is configured to identify the adapter based on the adapter identifier and transmit the action to the adapter. The broker also receives the reaction from the adapter and transmit the reaction to the application. The adapter is configured to acquire the data from the industrial automation environment based on an adapter instruction in the action, generate the reaction comprising the acquired data, and transmit the reaction to the broker.

Abstract: In an API conversion device 100, an API conversion unit 140 receives an API conversion instruction from an API-version-number management unit 120, acquires API definitions 21 to 23 and an API conversion program 24 with an API conversion DB access unit 150, converts a received API into a new version number, when the API conversion program was not successfully acquired, extracts a difference between acquired API definitions of new and old version numbers, and, when a new parameter is present in an API definition of the new version number, requests a service provision system 10 to give insufficient information, generates an API conversion program 25 of the new version number based on the insufficient information acquired from the service provision system 10 and the API definitions 21 to 23 of the new and old version numbers acquired from an API conversion DB 20, and converts the received API into the new version number based on the API definitions 21 to 23 and the API conversion program 25.

Abstract: An apparatus comprises a processing device configured to select prioritization criteria for a plurality of virtual computing resources and to determine, for at least one criterion in the selected prioritization criteria, at least one directional correlation between the at least one criterion and at least one other criterion in the selected prioritization criteria. The processing device is also configured to generate a prioritization of the plurality of virtual computing resources utilizing a multi-criteria decision analysis algorithm. The multi-criteria decision analysis algorithm is based at least in part on the determined at least one directional correlation. The processing device is further configured to perform one or more scheduling operations for the plurality of virtual computing resources based at least in part on the generated prioritization of the plurality of virtual computing resources.

Abstract: A method for managing cloud resource dependencies is described. The method may include receiving a resource configuration of a first resource. The method may include identifying a dependency of a first stage of a first resource on a second resource and performing a topological sort of a plurality of resources, based at least in part on the dependency of the first stage of the first resource. The method may include constructing a dependency graph including the plurality of resources, including the first stage of the first resource in a subordinate rank and the second resource in a superior rank, corresponding to the topological sort. The method may include generating an execution queue including the second resource in a priority execution position in the execution queue. The method may include executing the plurality of resources according to the execution queue.

Abstract: An event driven data processing system is disclosed that comprises event generators that generate events, an event queue that receives the events from the event generators, and an event router that receives the events from the event queue, and, for each event, selects a contextualizer based on an event type and transmits the event to a corresponding context queue associated with the selected contextualizer. The system also comprises context queues that receive the events from the event router and a plurality of contextualizers that receive the events from the context queues and, for each event, access context data sources, obtain additional context data, create a supplemented event, and store each supplemented event in an event datastore. The system further comprises a streaming component that streams each supplemented event from the event datastore for a period of time.

Abstract: A system and method receives a request for an event that is not fully specified, and predicts sufficient details of the event to instruct a hardware distributor to route the 5 request to an agent that can handle the predicted request.

Abstract: Provided are a method and apparatus for generating a topological graph, an anomaly detection method and apparatus, a device and a storage medium. The method for generating a topological graph includes acquiring a preset event stream, where the preset event stream corresponds to a normal log execution path; determining a dependent event pair in the preset event stream; determining a range of a transfer interval corresponding to the dependent event pair, where a transfer interval represents the time difference between adjacent occurrences of two events in the dependent event pair; and generating an event topological graph according to the range of the transfer interval and the transfer probability corresponding to the dependent event pair, where the transfer probability represents the conditional probability between the two events in the dependent event pair.