A manufacturing system state image preprocessing device in accordance with one embodiment of the present disclosure includes: a basic image generator configured to generate a basic image that visually represents a manufacturing system state based on manufacturing system state data, wherein the basic image includes a Gantt chart; and a conditioned image generator configured to generate one or more conditioned images in which one or more sets of conditions have been applied to the basic image, wherein an output image including at least one of the basic image and the one or more conditioned images is provided as input to an artificial neural network module.

Disclosed are an intelligent map-making system and device for a We-map, which mainly include an intelligent map-making system for a We-map and an intelligent making device on a mobile terminal. The system includes: a We-map natural interaction making module based on gesture interaction, voice interaction and eye movement interaction, a multi-modal interaction data fusion device, a user portrait building module, a We-map self-adaptive designer and a We-map intelligent generator. The device includes a We-map natural interaction interface designer, a We-map mapping interface optimizer, a We-map data processor, a We-map memory and a We-map user manager.

A method for creating a genogram of a family using touch and voice input includes: in response to a user touching a part of a touchscreen, generating a touch signal indicating a set of coordinates on the touchscreen at which a touch action occurred; recording a voice input from the user, the voice input including speech describing the family; obtaining an input text that is converted from the voice input; obtaining, using a generative language model based on a content of the input text, a genogram dataset in a format that is for generating the genogram; transforming the genogram dataset into a graphical genogram dataset; and creating the genogram based on the graphical genogram dataset, using the set of coordinates as a reference point, the genogram including at least one icon representing a member of the family.

Systems, methods, and computer-readable media are provided for triggering functionality on data to be generated in a user interface and/or data shown or visualized in a user interface based on a natural language request that references actions to be performed and data items to use in performing the actions. The user interface actions are triggered based on a structured object generated by a large language model (LLM), which may then be processed, validated, and used to carry out the actions. The LLM may be instructed to use control(s) of a displayed representation of a set of data, and the structured object generated by the LLM may cause updating, on the user interface, the displayed representation to reflect change(s) requested (e.g., to adjust filters, change a visualization or view, or zoom in or out on a set of multidimensional data). The control(s) may be selected from among representation transformation action(s) that are also available to be performed against the displayed representation via direct user input.

A system can be used to generate interactive data visualizations and textual content. The system receives a layout of a content item. The content item can be a data visualization dashboard or an article. The system can generate a content structure tree based on the layout. The content structure tree represents hierarchical and semantic relationships between sections of the content item. The system can receive input adding content elements, such as data visualizations or textual paragraphs, to sections within the content item. The system can identify text roles for different sections based on the content structure tree and the content elements. The system can generate text suggestions for the content item based on the text roles. The system can also generate text content for a text suggestion using a large language model, display the generated text content within the content item, and iteratively refine the content item.

According to the present disclosure provides a system and a method for converting a real-time information waveform based on real-time attack position and attack situation information of football matches and more specifically, converts a real-time information waveform based on a real-time attack position and attack situation information of football matches to provide infographic contents, that is, frequency type infographics, to allow fans who have difficulty in watching TV in real-time so that viewers may be easily synchronized with the broadcasted live football matches.

Literature on access control policies in cloud computing has focused on the design of secure models of access or on the syntactic and semantic analysis of policies but not into aspect of covert channel. A method and system for detecting covert channels in role based cloud access control policies using Large Language Model (LLM) is disclosed. A set of access control policies and an access specification is analyzed by the LLM for presence of violation indicating an implicit path between an entity (principal) and a restricted resource. Further, the LLM is prompted to generate a script Python program, which in turn generates a graph to visually depict paths leading from principal to one or more resources in the cloud environment, wherein any implicit access to the restricted resource if detected is highlighted by introducing a path from the principal to the restricted resources with label as covert channel. The covert channel so depicted provides information on possible theft threats.

Devices, systems, and methods for visually depicting a vessel and evaluating treatment options are disclosed. The methods can include obtaining pressure measurements from first and second instruments positioned within a vessel of a patient while the second instrument is moved longitudinally through the vessel from a first position to a second position and the first instrument remains stationary within the vessel; and outputting a visual representation of the pressure measurements obtained by the first and second instruments on a display, the output visual representation including a graphical display of a pressure ratio of the obtained pressure measurements and at least a portion of a pressure waveform of the obtained pressure measurements identifying a diagnostic period utilized in calculating the pressure ratio.

A computing device displays, on a user interface, a first visualization node and a text node. The first visualization node is upstream of the text node and includes a chart. In response to receiving a first user interaction with a portion of text content that is displayed in the text node, the device retrieving data of the first visualization node and transmits to a language model a first request that includes the data and the portion of text content. The device receives from the language model suggestions and data visualizations for analyzing the one or more datasets. The device displays the plurality of suggestions and their corresponding data visualizations on the user interface. The device receives user selection of a first suggestion that includes a first data visualization and renders a second visualization node on the user interface. The device displays the first data visualization in the second visualization node.

A computing device displays, on a user interface, a plurality of nodes, including a first visualization node and a second node. The first visualization node includes a chart. In response to receiving a user interaction with a portion of the chart, the device generates intermediate data according to the portion of the chart and displaying the intermediate data on the user interface. In response to receiving user selection of at least a subset of the intermediate data, the device transmits to a language model a request and receives, from the language model, data describing the one or more datasets according to the subset of the intermediate data selected by the user. The device renders the data describing the one or more datasets as (i) an update or modification of the first visualization node or the second node, or (ii) a third node that is distinct from the plurality of nodes.