Abstract: Systems and methods are disclosed for real time, frictionless channel switching to map and transpose a transaction on a preferred channel from an incoming channel. The systems and methods may use a machine learning model that processes features from a plurality of channels to determine the preferred channel. An omni channel processor is used to determine intended functionality data of the transaction for the preferred channel. The systems and methods may generate transposed intent data based on the intended functionality data of the transaction for the preferred channel. A deep link is generated and embedded with the transposed intent data and a channel access token for the transaction on the preferred channel. The deep link is configured to access and complete the requested transaction on the preferred channel.

Abstract: Systems and methods are disclosed for real time, frictionless channel switching to map and transpose a transaction on a preferred channel from an incoming channel. The systems and methods may use a machine learning model that processes features from a plurality of channels to determine the preferred channel. An omni channel processor is used to determine intended functionality data of the transaction for the preferred channel. The systems and methods may generate transposed intent data based on the intended functionality data of the transaction for the preferred channel. A deep link is generated and embedded with the transposed intent data and a channel access token for the transaction on the preferred channel. The deep link is configured to access and complete the requested transaction on the preferred channel.

Abstract: Systems and methods are disclosed for real time, frictionless channel switching to map and transpose a transaction on a preferred channel from an incoming channel. The systems and methods may use a machine learning model that processes features from a plurality of channels to determine the preferred channel. An omni channel processor is used to determine intended functionality data of the transaction for the preferred channel. The systems and methods may generate transposed intent data based on the intended functionality data of the transaction for the preferred channel. A deep link is generated and embedded with the transposed intent data and a channel access token for the transaction on the preferred channel. The deep link is configured to access and complete the requested transaction on the preferred channel.

Abstract: An apparatus may comprise a memory communicatively coupled to a processor. The processor may be configured to receive a request to perform multiple data processing operations and determine multiple sub-dialogues corresponding to the request. The sub-dialogues are part of a plurality of IVR operations. The processor may be further configured to route the request to a microservice of the microservices based at least in part upon the sub-dialogues. The microservice may be configured to fulfill the request. The processor may generate a response to the request associated with the microservice, update publishing commands in accordance with one or more rules and policies in response to generating the response, and publish the first microservice. The publishing commands associated with the microservice may be updated in isolation from the rest of the microservices.

Abstract: A system identifies data objects from a first piece of code in an original programming language and creates a knowledge graph that represents a relationship among the data objects. The system identifies a particular data object that is unique to the original programming language. The system determines a counterpart data object that is used for a particular purpose as the identified data object in a target programming language. The system creates a second piece of code in the target programming language by replacing the particular data object with the counterpart data object. The system determines if the second piece of code is configured to perform a task that the first piece of code is programmed to perform. In response to determining that the second piece of code is configured to perform the particular task, the system executes the second piece of code.

Abstract: A method for forwarding an alert includes receiving an alert in a first communication device over a first communication network, and forwarding the alert to a second communication device in a second communication network, the second communication network comprising a vehicle-to-vehicle communication network, the second communication device incapable of receiving the alert over the first communication network.

Abstract: A method for forwarding an alert includes receiving an alert in a first communication device over a first communication network, and forwarding the alert to a second communication device in a second communication network, the second communication network comprising a vehicle-to-vehicle communication network, the second communication device incapable of receiving the alert over the first communication network.

Abstract: An intelligent controllability check process can intelligently examine if enumeration of some possible values for a set of control signal inputs can be avoided (e.g., resulting in less than all possible values being enumerated, etc.). A modified intelligent QBF controllability check can be utilized, including a modified intelligent QBF solver. The process can include a formal controllability check with an extensive or exhaustive consideration of possible value assignments while avoiding enumeration of some possibilities. The formal controllability check can examine if a proof establishes a conclusion regarding assignment values. The proof can be utilized in determining possible results including: (1) a conclusion that signals provide controllability; (2) a conclusion that signals do not provide controllability; or (3) can not reach a conclusion one way or other if signals do or do not provide controllability. Results (e.g., SAT, UNSAT, etc.) of the QBF controllability check can be verified.