Abstract: Systems and methods described herein provide a computer-implemented approach for process simulations using multi-agent systems. Software agents are trained using historical process data associated with a process. Each software agent represents a single task in the process. Based on a candidate process model, the process is simulated to generate simulation results by executing a multi-agent system. The software agents operate autonomously within the multi-agent system based on trained behavior. The process is also executed using a runtime configuration that is based on the candidate process model. The execution of the process generates runtime results for comparison with the simulation results. In some examples, the candidate process model is adjusted based on the comparison, and the simulation and the execution of the process are repeated using an adjusted multi-agent system and an adjusted runtime configuration, respectively.

Abstract: Briefly, embodiments of a system, method, and article for receiving a structured data file and extracting object information from the structured data file. A graph structure may be built based, at least in part, on the extracted object information. One or more sentences may be created by traversing paths of the graph structure. The one or more created sentences may be provided to a Large Language Model (LLM) processor to generate one or more enhanced sentences. The one or more enhanced sentences may be output.

Abstract: Embodiments afford recommendations in the accurate modeling of complex process flows. A repository is provided of known models (in graph form) of complex processes. Semantics of the repository models, are constrained within an existing vocabulary (e.g., one that does not include a particular term). During an initial training phase, a fine-tuned sequence-to-sequence language model is generated from a pre-trained language model (e.g., T5) and semantics of the known repository process models, using transfer-learning techniques (e.g., from Natural Language Processing—NLP). During runtime, an incomplete process model (also in graph form) is received having an unlabeled node. Embodiments provide a node label recommendation based upon the fine-tuned sequence-to-sequence language model. The node label that is recommended, is in a vocabulary which extends beyond the repository vocabulary (e.g., includes the particular term). In this manner, accuracy and/or flexibility of modeling of complex processes (e.g.

Abstract: Mechanisms are disclosed for machine learning-based diagram label recognition in connection with diagrams represented by unstructured images. An unstructured image of the diagram is received. A plurality of text blocks associated with the diagram is detected. The text blocks are associated with labels contained within the diagram. Textual contents of the text blocks and the labels are recognized. The labels are associated with corresponding edges and shapes within the diagram.

Abstract: A software-based process modeling tool is provided that labels and links a plurality of activities forming part of a process that is being modeled include a recommendation engine. With the modeling tool, the activities are each represented as a node in the graphical user interface. A recommendation engine is polled with information characterizing the labeled activities and their corresponding links to obtain a plurality of ranked recommendations for an unlabeled node representing a next activity in the process for selection by a user. The recommendation engine applies the information characterizing the labeled activities and their corresponding links to a plurality of rules each having a corresponding confidence value. The plurality of rules is generated using a plurality of rule templates as applied to a plurality of historical processes each comprising a plurality of labeled and linked activities.

Abstract: Computer-readable media, methods, and systems are disclosed for semantic-aware rule-based recommendation within a process modeling system in which one or more recommendations are determined based on application of one or more rules to a process model at run-time. The rules are generated from logical formulas based on certain relations within predefined process model selections, from which semantic relationships between activity labels within the process model increase the flexibility of the recommendations. Flexibility of the recommendations is further increased by applying rules such that they are fulfilled in a semantically similar sense rather than a strict sense.

Abstract: Computer-readable media, methods, and systems are disclosed for converting a diagram into a digital diagram format. A diagram is received as an image file and a plurality of recognition stages produce a final diagram based on predicted information from one or more of the recognition stages. The plurality of recognition stages including a shape detection stage for detecting a plurality of shapes and at least one arrow detection stage in which arrows are detected as relations between pairs of shapes. The final diagram is generated based on the predicted information and is converted into the digital diagram format compatible with a diagram modeling language.

Abstract: Computer-readable media, methods, and systems are disclosed for converting a diagram into a digital diagram format. A diagram is received as an image file and a plurality of recognition stages produce a final diagram based on predicted information from one or more of the recognition stages. The plurality of recognition stages including a shape detection stage for detecting a plurality of shapes and at least one arrow detection stage in which arrows are detected as relations between pairs of shapes. The final diagram is generated based on the predicted information and is converted into the digital diagram format compatible with a diagram modeling language.

Abstract: Systems, methods, and computer programmable products are described herein for generating a robotic process automation bot script from a handwritten sketch. A digitally encoded image having a handwritten diagram with objects is received. The handwritten diagram is converted into a digital flowchart having a plurality of nodes. A confidence score is determined for the nodes based on (i) a textual similarity of contents of the node and a plurality of executable bot activities or (ii) a contextual similarity between a set of activities which measures how often they coappear in a plurality of reference bots. A robotic process automation bot script is generated by mapping the plurality of nodes to an executable bot activity of the plurality of executable bot activities based on the confidence score. The robotic process automation bot is then provided to a robotic process automation system for further modeling.

Abstract: A software-based process modeling tool is provided that labels and links a plurality of activities forming part of a process that is being modeled include a recommendation engine. With the modeling tool, the activities are each represented as a node in the graphical user interface. A recommendation engine is polled with information characterizing the labeled activities and their corresponding links to obtain a plurality of ranked recommendations for an unlabeled node representing a next activity in the process for selection by a user. The recommendation engine applies the information characterizing the labeled activities and their corresponding links to a plurality of rules each having a corresponding confidence value. The plurality of rules is generated using a plurality of rule templates as applied to a plurality of historical processes each comprising a plurality of labeled and linked activities.

Abstract: Systems, methods, and computer programmable products are described herein for generating a robotic process automation bot script from a handwritten sketch. A digitally encoded image having a handwritten diagram with objects is received. The handwritten diagram is converted into a digital flowchart having a plurality of nodes. A confidence score is determined for the nodes based on (i) a textual similarity of contents of the node and a plurality of executable bot activities or (ii) a contextual similarity between a set of activities which measures how often they coappear in a plurality of reference bots. A robotic process automation bot script is generated by mapping the plurality of nodes to an executable bot activity of the plurality of executable bot activities based on the confidence score. The robotic process automation bot is then provided to a robotic process automation system for further modeling.

Abstract: The present application relates to a pharmaceutical preparation comprising (a) from 0.15 to 3 weight percent of glyceryl trinitrate, (b) from 40 to 95 weight percent water, and (c1) from 2 to 10 weight percent of at least one water soluble polymer, or (c2) from 1 to 10 weight percent of at least one water soluble polymer and 5 to 20 weight percent of ethanol.

Abstract: Systems, methods, and devices are described herein for handwritten diagram recognition using machine learning. A machine learning component receives a digitally encoded image having a handwritten diagram. The machine learning component localizes and classifies a plurality of objects within the handwritten diagram. A structure recognition component identifies connections between each symbol of the plurality of objects based on content of the respective object. A handwriting recognition component interprets one or more alphanumeric text strings within a portion of the plurality of objects. A digital structured model of the digitally encoded image is automatically generated, without human intervention. The digital structured model has the identified connections among the plurality of objects and is in a computer-readable editable format.

Abstract: Systems, methods, and devices are described herein for handwritten diagram recognition using machine learning. A machine learning component receives a digitally encoded image having a handwritten diagram. The machine learning component localizes and classifies a plurality of objects within the handwritten diagram. A structure recognition component identifies connections between each symbol of the plurality of objects based on content of the respective object. A handwriting recognition component interprets one or more alphanumeric text strings within a portion of the plurality of objects. A digital structured model of the digitally encoded image is automatically generated, without human intervention. The digital structured model has the identified connections among the plurality of objects and is in a computer-readable editable format.

Abstract: The present application relates to a pharmaceutical preparation comprising (a) from 0.15 to 3 weight percent of glyceryl trinitrate, (b) from 40 to 95 weight percent water, and (c1) from 2 to 10 weight percent of at least one water soluble polymer, or (c2) from 1 to 10 weight percent of at least one water soluble polymer and 5 to 20 weight percent of ethanol.

Abstract: The present application relates to a pharmaceutical preparation comprising (a) from 0.15 to 3 weight percent of glyceryl trinitrate, (b) from 40 to 95 weight percent water, and (c1) from 2 to 10 weight percent of at least one water soluble polymer, or (c2) from 1 to 10 weight percent of at least one water soluble polymer and 5 to 20 weight percent of ethanol.

Abstract: The present application relates to a pharmaceutical preparation comprising (a) from 0.15 to 3 weight percent of glyceryl trinitrate, (b) from 40 to 95 weight percent water, and (c1) from 2 to 10 weight percent of at least one water soluble polymer, or (c2) from 1 to 10 weight percent of at least one water soluble polymer and 5 to 20 weight percent of ethanol.

Abstract: A method for operating a hearing system comprises the steps of: a) replacing the current settings by the former settings upon operation of a reset user control; and one of the steps of: b1) automatically replacing the former settings by new former settings upon receiving a request for adjusting at least one setting of the current settings, provided that no adjustment to the current settings has been carried out for at least a pre-defined time span up to the receiving of that request; or b2) automatically replacing the former settings by new former settings upon receiving a request for adjusting at least one setting of the current settings, provided that a difference between the current settings and the former settings caused by one or more adjustments to the current settings carried out during a pre-defined time span up to the receiving of that request is larger than a pre-defined difference.

Abstract: In order to provide a drier module for a drier for a coating plant, in particular for a coating plant for vehicle bodies, wherein the drier comprises a drier working space for receiving the objects to be dried, which space is bounded by a drier floor, a drier ceiling and lateral boundary walls, which reduces the transport costs for transporting the drier components from the production site to the erection site, it is proposed that the drier module comprise at least one section of a lateral boundary wall of the drier working space and one section of the drier floor and/or one section of the drier ceiling, wherein the drier floor section and/or the drier ceiling section are/is connected to the boundary wall section so as to be pivotable relative to the boundary wall section.

Abstract: A method for operating a hearing system (1) is described, the hearing system comprising a signal processor (12) controlled by settings of sound processing parameters referred to as current settings, wherein the current settings are stored in a first memory unit (18), and a second memory unit (19) comprises former settings.