Abstract: A system for determining corrosion under insulation of an industrial asset is provided. The system includes an infrared camera configured to acquire one or more time-series infrared images of an industrial asset. The system further includes a computing device configured to receive data characterizing the one or more time-series infrared images, and to identify an area of interest of the industrial asset within the one or more time-series infrared images. The computing device further configured to identify, by a machine learning algorithm, a plurality of defects within the area of interest based on pixel-wise assignment of at least one defect category selected from a plurality of defect categories associated with corrosion under insulation of the industrial asset, and to provide the plurality of defects within the area of interest of the industrial asset. Related methods, apparatuses, and computer-readable mediums are also provided.

Abstract: An apparatus, system and method of providing industrial analytics. The apparatus, system and method include at least a plurality of sensors sensing performance indicators for an industrial process across multiple nodes, wherein ones of the multiple nodes are remote from each other; at least one machine learning module comprising non-transitory computing code executed by a processor. When executed by the processor, the code causes the steps of: receiving user input regarding at least the industrial process and a data set; selecting a model based on at least the user input, wherein the selected model comprises a plurality of learnings based on the performance indicators sensed by multiple sensors across at least multiple ones of the multiple nodes; applying the selected model to the data set; assessing at least the performance indicators for the data set upon application of the selected model; and outputting the assessed performance indicator.

Abstract: Implementations include receiving, by a semantic translation service of a ML platform, an output data set from a ML model, the output data set including a predicted value and a set of metrics, determining, by the semantic translation service, a numerical value based on at least two or more metrics in the set of metrics, selecting, by the semantic translation service, a semantic result by mapping the numerical value to a projection including two or more semantic values, and transmitting, by the ML platform, a prediction result at least partially including the semantic result for selective display to a user using one or more user interfaces (UIs).

Abstract: In an embodiment, a volumetry method is provided. The method can include receiving one or more 2D images of a site including one or more containers configured to hold a liquid, the 2D images being acquired at a first time. The method can also include identifying a container within the 2D images. The method can further include selecting an identified container within the 2D images for volumetric analysis based upon a degree of occlusion of its front facing surface. The method can additionally include classifying a portion of the selected container containing the liquid. The method can further include determining the volume of liquid held within the container based upon the classified portion.

Abstract: The disclosure generally describes methods, software, and systems for providing solution descriptions. A problem description of a problem is received, from a client, at a cloud-based reasoning service. A solution description for a solution to the problem is received. Case metadata for a case defining the problem and solution are generated by the cloud-based reasoning service. The case metadata, including the problem description and solution description, are stored by the cloud-based reasoning service in a cases repository associating solutions with problems. A new problem is received at the cloud-based reasoning service. An automated analysis of the new problem is performed, and a comparison is made of the new problem with existing solutions in the cases repository to identify solutions matching the new problem. A new solution description is provided that is based on a match between the new problem description and the problem description and using the problem solution.

Abstract: Provided is a system and method which provides visually-compacted search results with attribute information embedded therein. In one example, the method may include receiving, via a user interface, a search request based on a set of attributes, identifying search results that match the search request based on attributes of the search results with respect to the set of attributes, and displaying, via the user interface, a plurality of circular objects corresponding to the plurality of search results, respectively, each circular object comprising a round-shaped outer bar arranged around an outer boundary of the circular object which includes attribute information of a search result corresponding to the circular object embedded therein.

Abstract: A method of analyzing an asset is provided. The method can include receiving first data characterizing an industrial asset. The first data can be acquired via a sensor. The method can also include determining a condition of the industrial asset based on a 3D digital twin of the industrial asset. The 3D digital twin can be generated using second data acquired prior to the first data. The digital twin can include at least one 3D digital instance of at least one component of the industrial asset and a list of components of the industrial asset described according to a pre-defined taxonomy associated with the industrial asset. The method can also include providing the condition of the industrial asset. Related apparatuses, systems, and computer-readable mediums are also provided.

Abstract: An apparatus, system and method of providing industrial analytics. The apparatus, system and method include at least a plurality of sensors sensing performance indicators for an industrial process across multiple nodes, wherein ones of the multiple nodes are remote from each other; at least one machine learning module comprising non-transitory computing code executed by a processor. When executed by the processor, the code causes the steps of: receiving user input regarding at least the industrial process and a data set; selecting a model based on at least the user input, wherein the selected model comprises a plurality of learnings based on the performance indicators sensed by multiple sensors across at least multiple ones of the multiple nodes; applying the selected model to the data set; assessing at least the performance indicators for the data set upon application of the selected model; and outputting the assessed performance indicator.

Abstract: A method includes receiving data characterizing a two-dimensional target site image including an image of a first asset acquired by a camera. The camera has a first location during the acquisition of the two-dimensional target site image. The method also includes receiving data characterizing a three-dimensional model of a target site that includes a plurality of assets including the first asset. The three-dimensional model is annotated to at least identify the first asset. The method further includes generating a projected annotation of the first asset on the two-dimensional target site image by at least projecting the three-dimensional model based on the first location and orientation of the camera relative to the first asset during the acquisition of the target site image.

Abstract: A method for determining a change in an asset and/or a characterization of an asset is provided. In an embodiment, the method can include receiving first data characterizing a target site including one or more assets. The method can also include generating a three-dimensional model of the target site based on the first data. The method can further include registering the first data with the three-dimensional model. The method can also include generating at least one three-dimensional projection onto at least one asset of the one or more assets included in the first data. The method can further include determining second data characterizing the at least one asset based on the at least on three-dimensional projection and providing the second data. In some embodiments, the method can be performed by systems or stored as instructions on computer readable mediums described herein.

Abstract: Computer vision based systems, and methods are provided for generating plume analysis data from a plurality of input image frames as captured by a camera. Image data associated with a plume of gas is received and provided as inputs to a predictive model used to determine plume analysis data including a plume prediction segmentation mask associated with the plume of gas. Other attributes of the plume are also estimated from the prediction segmentation mask such as cross-sectional area, cross-sectional velocity, leak source pixel and volumetric leak rates. The plume analysis data can be provided as an overlay atop the image data. The plume analysis data overlaid atop the image data can be transmitted by and/or to one or more computing devices.

Abstract: Implementations include receiving, by a semantic translation service of a ML platform, an output data set from a ML model, the output data set including a predicted value and a set of metrics, determining, by the semantic translation service, a numerical value based on at least two or more metrics in the set of metrics, selecting, by the semantic translation service, a semantic result by mapping the numerical value to a projection including two or more semantic values, and transmitting, by the ML platform, a prediction result at least partially including the semantic result for selective display to a user using one or more user interfaces (UIs).

Abstract: The disclosure generally describes methods, software, and systems for providing solution descriptions. A problem description of a problem is received, from a client, at a cloud-based reasoning service. A solution description for a solution to the problem is received. Case metadata for a case defining the problem and solution are generated by the cloud-based reasoning service. The case metadata, including the problem description and solution description, are stored by the cloud-based reasoning service in a cases repository associating solutions with problems. A new problem is received at the cloud-based reasoning service. An automated analysis of the new problem is performed, and a comparison is made of the new problem with existing solutions in the cases repository to identify solutions matching the new problem. A new solution description is provided that is based on a match between the new problem description and the problem description and using the problem solution.

Abstract: Provided is a system and method which provides visually-compacted search results with attribute information embedded therein. In one example, the method may include receiving, via a user interface, a search request based on a set of attributes, identifying search results that match the search request based on attributes of the search results with respect to the set of attributes, and displaying, via the user interface, a plurality of circular objects corresponding to the plurality of search results, respectively, each circular object comprising a round-shaped outer bar arranged around an outer boundary of the circular object which includes attribute information of a search result corresponding to the circular object embedded therein.

Abstract: The disclosure generally describes methods, software, and systems for providing solution descriptions. A problem description of a problem is received, from a client, at a cloud-based reasoning service. A solution description for a solution to the problem is received. Case metadata for a case defining the problem and solution are generated by the cloud-based reasoning service. The case metadata, including the problem description and solution description, are stored by the cloud-based reasoning service in a cases repository associating solutions with problems. A new problem is received at the cloud-based reasoning service. An automated analysis of the new problem is performed, and a comparison is made of the new problem with existing solutions in the cases repository to identify solutions matching the new problem. A new solution description is provided that is based on a match between the new problem description and the problem description and using the problem solution.

Abstract: In an embodiment, a volumetry method is provided. The method can include receiving one or more 2D images of a site including one or more containers configured to hold a liquid, the 2D images being acquired at a first time. The method can also include identifying a container within the 2D images. The method can further include selecting an identified container within the 2D images for volumetric analysis based upon a degree of occlusion of its front facing surface. The method can additionally include classifying a portion of the selected container containing the liquid. The method can further include determining the volume of liquid held within the container based upon the classified portion.

Abstract: Disclosed herein are system, method, and computer program product embodiments for obtaining feedback in an explicit, non-disruptive manner. An embodiment operates by determining a trigger corresponding to a feedback event, where the trigger is associated with a particular application that is registered with a feedback application associated with the feedback event; detecting an application event corresponding to the trigger occurs during an execution of the particular application; receiving a screenshot of a user interface of the particular application at a time of the detecting; providing a notification indicating that feedback corresponding to the application event is requested; receiving a request to launch the feedback event; and receiving feedback corresponding to the feedback event via the feedback application.

Abstract: The present disclosure provides improved particle processing (e.g., cytometry and/or cell purification) systems and methods that can operate in an autonomous fashion. More particularly, the present disclosure provides for assemblies, systems and methods for analyzing, sorting, and/or processing (e.g., purifying, measuring, isolating, detecting and/or enriching) particles (e.g., cells, microscopic particles, etc.) where human intervention is not required and/or is minimized. The systems, assemblies and methods of the present disclosure advantageously improve run performance of particle processing systems (e.g., cell purification systems, cytometers) by significantly reducing and/or substantially eliminating the burden of operation for human intervention by automating numerous functions, features and/or steps of the disclosed systems and methods.

Abstract: Disclosed herein are system, method, and computer program product embodiments for implementing facet components and facet collection components for dynamic switching between display contexts. An embodiment operates by presenting, via a first rendering component, a first graphical representation of a numeric component in a first display context within a graphical user interface, determining a second display context associated with the numeric component, and loading a second rendering component associated with the second display context into the numeric component. Further, the embodiment presents, via the second rendering component, a second graphical representation of the numeric component in the second display context within the graphical user interface.

Abstract: The disclosure generally describes methods, software, and systems for providing solution descriptions. A problem description of a problem is received, from a client, at a cloud-based reasoning service. A solution description for a solution to the problem is received. Case metadata for a case defining the problem and solution are generated by the cloud-based reasoning service. The case metadata, including the problem description and solution description, are stored by the cloud-based reasoning service in a cases repository associating solutions with problems. A new problem is received at the cloud-based reasoning service. An automated analysis of the new problem is performed, and a comparison is made of the new problem with existing solutions in the cases repository to identify solutions matching the new problem. A new solution description is provided that is based on a match between the new problem description and the problem description and using the problem solution.