Methods and systems for generating a computer program for a governance, risk, compliance (GRC) system are described. In an example, a processor may detect a change among a plurality of objects in the GRC system. The processor may generate a snapshot of the plurality of objects in response to the detected change. The snapshot may include the detected change among the plurality of objects. The processor may train a machine learning model using the snapshot. The trained machine learning model may indicate relationships among a set of related objects, where the related objects may be among the plurality of objects. The processor may generate a computer program based on the trained machine learning model. The computer program may include a set of instructions for setting a field value of an object among the set of related objects.

In some embodiments, a method comprises receiving, at a processor of an autonomous vehicle and from at least one sensor, sensor data distributed within a time window. A first event being a first event type occurring at a first time in the time window is identified by the processor using a software model based on the sensor data. At least one first attribute associated with the first event is extracted by the processor. A second event being the first event type occurring at a second time in the time window is identified by the processor based on the at least one first attribute. In response to determining that the second event is not yet recognized as being the first event type, a first label for the second event is generated by the processor.

A method for automatically generating sample code for an API for payment processing in a payment network includes reading an acquirer processor-specific API for payment processing in a payment network using an acquirer processor-specific API reader, generating acquirer processor-specific API data using the acquirer processor-specific API reader, converting the acquirer processor-specific API data into a format compatible with an output generator, and generating language-specific sample code by the output generator using the converted acquirer processor-specific API data and a language-specific template.

A method for automatically generating sample code for an API for payment processing in a payment network includes reading an acquirer processor-specific API for payment processing in a payment network using an acquirer processor-specific API reader, generating acquirer processor-specific API data using the acquirer processor-specific API reader, converting the acquirer processor-specific API data into a format compatible with an output generator, and generating language-specific sample code by the output generator using the converted acquirer processor-specific API data and a language-specific template.

In an example in accordance with the present disclosure, a system is described. The system includes a data collector to collect usage data for the electronic device over a first period of time. The system also includes a model generator. The model generator extrapolates usage data for the electronic device over a second period of time that is longer than the first period of time and predicts a state of the electronic device based on extrapolated usage data for the electronic device over the second period of time.

A method for establishing a social network provides a user to prepare a deliverable work system and delivery the deliverable work system to other users to associate the deliverable work system. The delivering step may be repeatable by the user and the other users to establish a direct-link relationship of the deliverable work system and each of the other users, such that the user and the other users are able to work together in the deliverable work system. And a home system for hosting and managing the deliverable work system owned by the user may have a social network system with a associated second home system owned by any of the other users by the deliverable work system.

A method for establishing a social network provides a user to prepare a deliverable work system and delivery the deliverable work system to other users to associate the deliverable work system. The delivering step may be repeatable by the user and the other users to establish a direct-link relationship of the deliverable work system and each of the other users, such that the user and the other users are able to work together in the deliverable work system. And a home system for hosting and managing the deliverable work system owned by the user may have a social network system with a associated second home system owned by any of the other users by the deliverable work system.

A finite state automata (FSA) may comprise of a plurality of states and a plurality of events that are triggered to transition between the plurality of states to enable the continuous delivery of one or more machine learning (ML) models. Datasets may be uploaded by one or more users to a computing device. Each dataset may include columns of attributes and/or rows of data for each attribute. Each dataset may be analyzed according to respective predefined ML model criteria. Each dataset may be automatically transformed and/or enhanced to meet the predefined ML model criteria. Data analysis may be performed on each dataset to inform the building of the ML models. An algorithm may be received for each ML model. Each ML model may be built based on the respective dataset and the respective algorithm to generate an ML model file. Logs may be stored for tracking the process performed by the FSA.

A method includes obtaining a binary code of a controller. The method also includes decompiling the binary code of the controller to generate a source code. The method further includes generating one or more abstract syntax trees based on the source code. The method further includes generating an interpretable model based on the one or more abstract syntax trees. The interpretable model is interpretable by subject matter experts.

Provided are methods and systems for combining business process management (BPM) and robotic process automation (RPA) into a unified BPM and RPA process. An example method commences with creating a BPM process flow. The BPM process flow can include one or more BPM models for executing BPM tasks. The method then proceeds with creating an RPA process flow. The RPA process flow can include one or more RPA models for executing the one or more RPA tasks. The method can further include linking the one or more RPA models to the BPM process flow. Thereafter, the method proceeds with creating an application package associated with the unified BPM and RPA process. The application package can include the one or more BPM models and the one or more RPA models. The method can further include exporting the application package for deployment.