A human-machine interface (HMI), HMI system, turbomachinery package, and method of modifying a partition of an HMI are disclosed. The HMI comprises a first partition storing a first operating system exclusively supporting a primary application; and a second partition storing a second operating system exclusively supporting an imaging application. The HMI system comprises the HMI; an external computing device; a serial cable; and, optionally, a network cable. The turbomachinery package comprises a housing; a gas turbine; a plurality of sensors; a plurality of actuators; and an HMI. The imaging application may be an image deploy function, an image back-up function, and/or an image restore function, any of which can be executed without the use of removable media.

The disclosed technology is generally directed to IoT technology. In one example of the technology, the following actions are performed for each module of a plurality of modules on a first edge device. An identification message that includes information associated with identification of the module is received. The validity of the module is then verified. After the module is verified, based at least in part on the identification message, an IoT support service is selected from a plurality of IoT support services. The module is then caused to be registered with the selected IoT support service. The plurality of modules are compositable together into an application for the first edge device. The modules of the plurality of modules are capable of being used interoperably with other modules without altering the other modules.

A non-transitory computer-readable medium stores computer-readable instructions that are executable by a processor of a first terminal device compatible with a first platform, the instructions being configured to, when executed by the processor, cause the first terminal device to accept selection of an image processing apparatus connected with the first terminal device, accept selection of a function to be set up on the first terminal device from among one or more functions executable by the image processing apparatus, install, into the first terminal device, a first program compatible with the image processing apparatus and the first platform, and output an access information image. The access information image represents access information based on the selected function and an address of a web page representing a site of a supply source for a second program compatible with the image processing apparatus and a second platform.

Methods and systems are presented for consuming different data sources, and deploying artificial intelligence and machine learning programs on different target devices or infrastructures. Many data types can be transformed into machine learning data shards (MLDS) while many machine learning programs written in various programming languages or frameworks are transformed to common operator representations. Operator representations are transformed into execution graphs (EG) for a chosen target device or infrastructure. The MLDS and EG are input to the targeted devices and infrastructures, which then execute the machine learning programs (now transformed to EGs) on the MLDS to produce trained models or predictions with trained models.

The disclosed technology is generally directed to communications in an IoT environment. In one example of the technology, a plurality of module twins that respectively correspond to a plurality of modules of edge applications on a plurality of edge devices are stored. The plurality of module twins individually include metadata associated with the corresponding module of the plurality of modules. At least one module of the plurality of modules to be modified by adding a declarative rule is determined, such that the declarative rule causes determining whether an event has been triggered based on a particular event having been determined to have occurred, and, in response to the triggering of the event, communicating the triggering of the event to at least one declarative target. The determined at least one module of the plurality of modules is caused to be modified by adding the declarative rule.

A system and method of holistic application development and deployment in a distributed, heterogeneous computing environment. The method includes identifying an individual component from among a plurality of components in a target system as an identified component of a plurality of identified components, mapping each one of the identified components to respective ones of a target hardware node, generating intermediate code for each respective one of the target hardware nodes, generating serialization code for each respective communication interface between the target hardware nodes, transmitting the respective intermediate codes to each one of the target hardware nodes, and transmitting respective serialization codes to each communication interface of the target hardware nodes.

Provided is a software packaging device, which sets an initial environment, migrates software information used by a target software to the initial environment, collects hardware information from an operation system at which the software is installed, applies the hardware information to the initial environment, and generates a software package from the initial environment to which the software information and the hardware information are applied.

Disclosed herein are system, method, and computer program product embodiments for generating software artifacts operable across diverse platforms from a single conceptual data model. The conceptual data model may be enhanced with metadata that allows the creation of platform-specific logical data models containing additional metadata that is leveraged to create deployable software artifacts. An organization may subsequently modify the conceptual data model and all relevant software artifacts may be updated and redeployed across all integrated platforms. Such a conceptual data model further facilitates the creation of documentation describing data entities in the organization's technical infrastructure, the creation of mapping files for use by a data exchange system, and the processing of federated queries that gather data from multiple data stores across a data landscape.

The present application is directed towards systems and methods for identifying and grouping code objects into functional areas with boundaries crossed by entry points. An analysis agent may select a first functional area of a source installation of an application to be transformed to a target installation of the application from a plurality of functional areas of the source installation, each functional area comprising a plurality of associated code objects; and identify a first subset of the plurality of associated code objects of the first functional area having associations only to other code objects of the first functional area, and a second subset of the plurality of associated code objects of the first functional area having associations to code objects in additional functional areas, the second subset comprising entry points of the first functional area.

This disclosure relates to customizing deployment of an application to a user interface of a client device. An exemplary method generally includes training a model based on historical context information of a plurality of users by identifying correlations between the historical context information and a plurality of widgets and storing the correlations in the model. The method further includes receiving context information from the client device. The method further includes determining a user intent based on the context information using the model. The method further includes selecting one or more widgets to include in a custom user interface definition based, at least in part, on the user intent. The method further includes transmitting, to the user interface of the client device, the custom user interface definition.