Abstract: A method controls execution of an intended application. One or more processors receive a first formatted character string that is in a first format. The processor(s) determine which application from multiple applications is an intended application that is to use the first formatted character string as a basis of an input to the intended application. The processor(s) convert the first formatted character string into a second formatted character string by applying a second format that is used by the intended application, and then execute the intended application by using the second formatted character string as an input to the intended application.

Abstract: An interface superpipe is implemented in a filesystem. A filesystem in a kernel, receives a command to open a file, the command issued in the execution of a process in an application. The file is determined to be on an interface disk. It is determined that a context does not exist for the process and, in response, an adapter queue is allocated for the process in a kernel memory and mapped into a process address space associated with the process. The context information of the process is saved in the kernel memory. The filesystem may be part of a system further comprising a processor, a storage, an interface adapter in communication with the storage and sharing a memory space with the processor, and an application in communication with the filesystem.

Abstract: Embodiments generally relate an intelligent automated trolley system. In some embodiments, a method includes receiving a trolley request. The method further includes determining one or more luggage characteristics of one or more luggage items. The method further includes determining one or more trolleys to send based on the luggage characteristics of the one or more luggage items. The method further includes assigning the one or more trolleys to assist the user based on the one or more characteristics of the one or more luggage items. The method further includes sending the one or more trolleys to a meeting location.

Abstract: An approach for outage avoidance. The approach receives a scheduled task, wherein the scheduled task is completed at a scheduled time by a device. The approach receives an outage time of a service disruption, wherein the service disruption occurs at the outage time. The approach determines whether the service disruption conflicts with the scheduled task, based on the outage time and the scheduled time. Responsive to a determination that the service disruption conflicts with the scheduled task, the approach modifies the scheduled task to be completed at a modified time, wherein the outage time does not conflict with the modified time.

Abstract: A method controls execution of an intended application. One or more processors receive a first formatted character string that is in a first format. The processor(s) determine which application from multiple applications is an intended application that is to use the first formatted character string as a basis of an input to the intended application. The processor(s) convert the first formatted character string into a second formatted character string by applying a second format that is used by the intended application, and then execute the intended application by using the second formatted character string as an input to the intended application.

Abstract: A method for managing an execution of a workload within a networked computing environment. The method includes at least one computer processor identifying a plurality of objects associated with a workload, the plurality of objects includes a first object. The method further includes identifying information corresponding to one or more one nodes that store an instance of the first object, where the information identifies features of a node. The method further includes identifying an embedded computing entity associated with processing at least the first object. The method further includes deploying an instance of the identified embedded computing entity to a first node that stores an instance of the first object based on information associated with features of the first node. The method further includes executing the workload utilizing the embedded computing entity.

Abstract: An approach using one or more computer processors to send a request from a user for a mobile payment to a payment gateway and to determine that an event has occurred on a mobile computing device of a user. The approach includes sending a request for additional transaction time for the mobile payment.

Abstract: Aspects of the invention perform an operation comprising receiving a plurality of rules associated with a first seat in a mass-transit vehicle, determining a plurality of physical attributes for a first passenger, of a plurality of passengers, based on data describing the first passenger received from a plurality of data sources, determining a plurality of non-physical attributes for the first passenger based on the received data describing the first passenger, determining that at least one of the plurality of physical attributes and the plurality of non-physical attributes of the first passenger satisfy each rule in the set of rules associated with the first seat, computing, based on a machine learning (ML) model a score for the first passenger, determining that the score exceeds a threshold score associated with the first seat, and allocating the first passenger to the first seat in the mass-transit vehicle.

Abstract: Embodiments generally relate an intelligent automated trolley system. In some embodiments, a method includes receiving a trolley request. The method further includes determining one or more luggage characteristics of one or more luggage items. The method further includes determining one or more trolleys to send based on the luggage characteristics of the one or more luggage items. The method further includes assigning the one or more trolleys to assist the user based on the one or more characteristics of the one or more luggage items. The method further includes sending the one or more trolleys to a meeting location.

Abstract: A conference management application for a remote conferencing system stores information on a plurality of users and a plurality of client devices though which the plurality of users communicate with the remote conferencing system. The conference management application transmits information for a remote conference to a user, wherein the information that is transmitted is generated by a cognitive engine via learning mechanisms that iteratively incorporate information on previously completed remote conferences, information on the user, and information on the client device used by the user to communicate with the conference management application.

Abstract: Determination of a degree of similarity among and between a set of text notation schema instances. One type of text notation schema instance is the JSON type. In some embodiments, the degree of similarity is expressed as a schema variance value which is determined by individually comparing the schema instances of the set of text notation schema instances to a representative majority schema. Also, determining a quality of a data source associated with the plurality of text notation schema instances based, at least in part, upon the similarity value.

Abstract: An interface superpipe is implemented in a filesystem. A filesystem in a kernel, receives a command to open a file, the command issued in the execution of a process in an application. The file is determined to be on an interface disk. It is determined that a context does not exist for the process and, in response, an adapter queue is allocated for the process in a kernel memory and mapped into a process address space associated with the process. The context information of the process is saved in the kernel memory. The filesystem may be part of a system further comprising a processor, a storage, an interface adapter in communication with the storage and sharing a memory space with the processor, and an application in communication with the filesystem.

Abstract: Systems, methods, and computer program products to perform an operation comprising receiving a plurality of rules associated with a first seat in a mass-transit vehicle, determining a plurality of physical attributes for a first passenger, of a plurality of passengers, based on data describing the first passenger received from a plurality of data sources, determining a plurality of non-physical attributes for the first passenger based on the received data describing the first passenger, determining that at least one of the plurality of physical attributes and the plurality of non-physical attributes of the first passenger satisfy each rule in the set of rules associated with the first seat, computing, based on a machine learning (ML) model a score for the first passenger, determining that the score exceeds a threshold score associated with the first seat, and allocating the first passenger to the first seat in the mass-transit vehicle.

Abstract: An approach for joining operations on document-oriented databases. The approach consists of receiving database identifiers, common attributes and results attributes for core and target databases being joined. Common attributes are searched for in the databases. The searches performed include string, expansive, character and nested. Common attribute join conflicts are identified and input is received to resolve attribute join conflicts. Resolved join conflicts are updated in a join substitution database for subsequent use and joined data results are output to virtual table(s).

Abstract: A computing system is configured to process at least one voice input of a user and output an audio result. The computing system comprises at least one microphone configured to receive the voice input from the user. The computing system further comprises at least one processor configured to at least interpret the voice input and generate the audio result. The computing system also comprises an output speaker device configured to output the audio result. The audio result includes a description of whether one or more behavioral health states associated with the user have been detected.

Abstract: A computing system is configured to process at least one voice input of a user and output an audio result. The computing system comprises at least one microphone configured to receive the voice input from the user. The computing system further comprises at least one processor configured to at least interpret the voice input and generate the audio result. The computing system also comprises an output speaker device configured to output the audio result. The audio result includes a description of whether one or more behavioral health states associated with the user have been detected.

Abstract: A computing system is configured to process at least one voice input of a user and output an audio result. The computing system comprises at least one microphone configured to receive the voice input from the user. The computing system further comprises at least one processor configured to at least interpret the voice input and generate the audio result. The computing system also comprises an output speaker device configured to output the audio result. The audio result includes a description of whether one or more behavioral health states associated with the user have been detected.

Abstract: A computing system is configured to process at least one voice input of a user and output an audio result. The computing system comprises at least one microphone configured to receive the voice input from the user. The computing system further comprises at least one processor configured to at least interpret the voice input and generate the audio result. The computing system also comprises an output speaker device configured to output the audio result. The audio result includes a description of whether one or more behavioral health states associated with the user have been detected.

Abstract: An approach for outage avoidance. The approach receives a scheduled task, wherein the scheduled task is completed at a scheduled time by a device. The approach receives an outage time of a service disruption, wherein the service disruption occurs at the outage time. The approach determines whether the service disruption conflicts with the scheduled task, based on the outage time and the scheduled time. Responsive to a determination that the service disruption conflicts with the scheduled task, the approach modifies the scheduled task to be completed at a modified time, wherein the outage time does not conflict with the modified time.

Abstract: An approach for outage avoidance. The approach receives a scheduled task, wherein the scheduled task is completed at a scheduled time by a device. The approach receives an outage time of a service disruption, wherein the service disruption occurs at the outage time. The approach determines whether the service disruption conflicts with the scheduled task, based on the outage time and the scheduled time. Responsive to a determination that the service disruption conflicts with the scheduled task, the approach modifies the scheduled task to be completed at a modified time, wherein the outage time does not conflict with the modified time.