Abstract: A system and method are disclosed for predicting recommendations for a user interface. The method includes generating a graphical user interface that receives an input from a user of a client portal, crawling tasks associated with the user in the client portal, ranking the tasks according to an intent associated with the input from the user, fetching at least one task from the ranked tasks, calculating a quantity of steps to complete the task from the ranked tasks; identifying one or more slots used by the task in at least one step from the quantity of steps, and generating one or more recommendations comprising a subsequent action for the user to complete the task.

Abstract: A system and method are disclosed for predicting recommendations for a user interface. The method includes generating a graphical user interface that receives an input from a user of a client portal, crawling tasks associated with the user in the client portal, ranking the tasks according to an intent associated with the input from the user, fetching at least one task from the ranked tasks, calculating a quantity of steps to complete the task from the ranked tasks; identifying one or more slots used by the task in at least one step from the quantity of steps, and generating one or more recommendations comprising a subsequent action for the user to complete the task.

Abstract: A system and method are disclosed for computer vision in-store planogram analysis. The system includes a retail entity comprising a product display area defined by a planogram, and a planogram analyzer comprising a server which trains a machine learning model to generate recommendations to optimize one or more planogram metrics using historical data and computer vision data. The system generates, by the trained machine learning model, recommendations to optimize the one or more planogram metrics, and alters the planogram based on the one or more recommendations. The system further uses the trained machine learning model with a probabilistic optimization technique approximating a global optimum to generate the one or more recommendations to optimize the one or more planogram metrics. The computer vision includes one or more of eyeball movement, eyeball engagement and eyeball lingering time.

Abstract: A system and method are disclosed to generate mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and configured to select data stored in a data table coupled to the computer. Embodiments select one or more key process indicators (KPIs), dimensions by which to display the selected data, and color schemes by which to display the selected data. Embodiments generate a first mixed-reality object displaying the selected data according to the selected one or more KPIs, dimensions, and color schemes, and a second mixed-reality object displaying the selected data as a three-dimensional model of nodes and connections. Embodiments display the first and second mixed-reality objects on a display device, and manipulate one of the first and second mixed-reality objects in response to input received by one or more sensors.

Abstract: Various examples are directed to systems and methods for managing network traffic between a user query machine and a database query machine. A data center network controller may generate a plurality of query type scores describing database query type types directable from the user query machine to the database query machine. The data center network controller may generate a first database element score for a first database element. The first database element score may be based at least in part on a set of the query type scores associated with database queries to be executed at the first database element and on a first schema weight of a first schema associated with the first database element. The data center network controller may assign a first database element traffic flow to a first network appliance queue based at least in part on the first database element score.

Abstract: A system and method are disclosed for predicting recommendations for a user interface. The method includes generating a graphical user interface that receives an input from a user of a client portal, crawling tasks associated with the user in the client portal, ranking the tasks according to an intent associated with the input from the user, fetching at least one task from the ranked tasks, calculating a quantity of steps to complete the task from the ranked tasks; identifying one or more slots used by the task in at least one step from the quantity of steps, and generating one or more recommendations comprising a subsequent action for the user to complete the task.

Abstract: A system and method are disclosed for computer vision in-store planogram analysis. The system includes a retail entity comprising a product display area defined by a planogram, and a planogram analyzer comprising a server which trains a machine learning model to generate recommendations to optimize one or more planogram metrics using historical data and computer vision data. The system generates, by the trained machine learning model, recommendations to optimize the one or more planogram metrics, and alters the planogram based on the one or more recommendations. The system further uses the trained machine learning model with a probabilistic optimization technique approximating a global optimum to generate the one or more recommendations to optimize the one or more planogram metrics. The computer vision includes one or more of eyeball movement, eyeball engagement and eyeball lingering time.

Abstract: A system and method are disclosed to generate mixed-reality visualizations and objects to identify exceptions within large volumes of data and provide resolution options. Embodiments include a computer comprising a processor and memory and a mixed-reality display device comprising a display and one or more sensors. Embodiments generate a first mixed-reality object comprising a first cuboid comprising one or more adjustable display dimensions and one or more cubelets divided along at least one of the one or more adjustable display dimensions. Embodiments display the first mixed-reality object on the display and transform one or more cubelets of the first cuboid in response to a first sensor input. Embodiments identify one or more exceptions, generate one or more resolution options to resolve at least one of the one or more exceptions, and display the transformed one or more cubelets of the first cuboid and the one or more resolution options.

Abstract: A system and method are disclosed to generate mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and configured to select data stored in a data table coupled to the computer. Embodiments select one or more key process indicators (KPIs), dimensions by which to display the selected data, and color schemes by which to display the selected data. Embodiments generate a first mixed-reality object displaying the selected data according to the selected one or more KPIs, dimensions, and color schemes, and a second mixed-reality object displaying the selected data as a three-dimensional model of nodes and connections. Embodiments display the first and second mixed-reality objects on a display device, and manipulate one of the first and second mixed-reality objects in response to input received by one or more sensors.

Abstract: A system and method are disclosed to generate one or more mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and a mixed-reality display device comprising a display and one or more sensors. Embodiments generate a mixed-reality object comprising a first cuboid, the first cuboid comprising one or more adjustable display dimensions corresponding to one or more key process indicators (KPIs) and one or more cubelets divided along at least one of the one or more adjustable display dimensions. Embodiments display the mixed-reality object on the display, and adjust at least one of the one or more adjustable display dimensions in response to receiving a first input to the one or more sensors. In response to a second input, embodiments transform the one or more cubelets of the first cuboid.

Abstract: A system and method are disclosed to generate mixed-reality visualizations and objects to identify exceptions within large volumes of data and provide resolution options. Embodiments include a computer comprising a processor and memory and a mixed-reality display device comprising a display and one or more sensors. Embodiments generate a first mixed-reality object comprising a first cuboid comprising one or more adjustable display dimensions and one or more cubelets divided along at least one of the one or more adjustable display dimensions. Embodiments display the first mixed-reality object on the display and transform one or more cubelets of the first cuboid in response to a first sensor input. Embodiments identify one or more exceptions, generate one or more resolution options to resolve at least one of the one or more exceptions, and display the transformed one or more cubelets of the first cuboid and the one or more resolution options.

Abstract: A system and method are disclosed for virtual planogram automation with computer vision, comprising a retail entity comprising a product display area; and a planogram planner configured to access images of products prior to the display of the products in the product display area, classify the images by using a convolutional neural network, assign a bounding box to the products identified in the images, localize and detect objects and estimate product dimensions corresponding to the objects, determine changes in the estimated product dimensions by comparing the estimated product dimensions with corresponding baseline product dimensions to determine whether product dimensions has changed, and determine a total area remaining in a simulated planogram for alternative product placements after factoring in the determined changes in product dimensions.

Abstract: A system and method are disclosed to generate one or more mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and a mixed-reality display device comprising a display and one or more sensors. Embodiments generate a mixed-reality object comprising a first cuboid, the first cuboid comprising one or more adjustable display dimensions corresponding to one or more key process indicators (KPIs) and one or more cubelets divided along at least one of the one or more adjustable display dimensions. Embodiments display the mixed-reality object on the display, and adjust at least one of the one or more adjustable display dimensions in response to receiving a first input to the one or more sensors. In response to a second input, embodiments transform the one or more cubelets of the first cuboid.

Abstract: A system and method are disclosed for virtual planogram automation with computer vision, comprising a retail entity comprising a product display area; and a planogram planner configured to access images of products prior to the display of the products in the product display area, classify the images by using a convolutional neural network, assign a bounding box to the products identified in the images, localize and detect objects and estimate product dimensions corresponding to the objects, determine changes in the estimated product dimensions by comparing the estimated product dimensions with corresponding baseline product dimensions to determine whether product dimensions has changed, and determine a total area remaining in a simulated planogram for alternative product placements after factoring in the determined changes in product dimensions.

Abstract: The present disclosure relates to a method of detecting crack propagation in a wall of a metallurgical furnace by a detection unit. The detection unit is configured to extract one or more dominant frequency parameters from the corresponding reflected stress signal, and analysing, a phase from each dominant frequency parameters. The analysing of the phase comprises determines, one or more coefficients for each dominant frequency parameters. The detection unit then identifies, a dominant phase based on the corresponding one or more coefficients and selects a frequency relevant to a thickness parameter based on the dominant phase. The crack propagation in the wall of the metallurgical furnace is then detected based on the frequency relevant to the thickness parameter at each of the one or more locations. The present disclosure provides an accurate method for determining condition of refractory lining by elimination unwanted noise signals.

Abstract: A system and method are disclosed to generate mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and configured to select data stored in a data table coupled to the computer. Embodiments select one or more key process indicators (KPIs), dimensions by which to display the selected data, and color schemes by which to display the selected data. Embodiments generate a first mixed-reality object displaying the selected data according to the selected one or more KPIs, dimensions, and color schemes, and a second mixed-reality object displaying the selected data as a three-dimensional model of nodes and connections. Embodiments display the first and second mixed-reality objects on a display device, and manipulate one of the first and second mixed-reality objects in response to input received by one or more sensors.

Abstract: A system and method are disclosed to generate one or more mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and a mixed-reality display device comprising a display and one or more sensors. Embodiments generate a mixed-reality object comprising a first cuboid, the first cuboid comprising one or more adjustable display dimensions corresponding to one or more key process indicators (KPIs) and one or more cubelets divided along at least one of the one or more adjustable display dimensions. Embodiments display the mixed-reality object on the display, and adjust at least one of the one or more adjustable display dimensions in response to receiving a first input to the one or more sensors. In response to a second input, embodiments transform the one or more cubelets of the first cuboid.

Abstract: A system and method are disclosed to generate mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and configured to select data stored in a data table coupled to the computer. Embodiments select one or more key process indicators (KPIs), dimensions by which to display the selected data, and color schemes by which to display the selected data. Embodiments generate a first mixed-reality object displaying the selected data according to the selected one or more KPIs, dimensions, and color schemes, and a second mixed-reality object displaying the selected data as a three-dimensional model of nodes and connections. Embodiments display the first and second mixed-reality objects on a display device, and manipulate one of the first and second mixed-reality objects in response to input received by one or more sensors.

Abstract: A system and method are disclosed to generate one or more mixed-reality visualizations and objects to facilitate efficient interaction with large volumes of data. Embodiments include a computer comprising a processor and memory and a mixed-reality display device comprising a display and one or more sensors. Embodiments generate a mixed-reality object comprising a first cuboid, the first cuboid comprising one or more adjustable display dimensions corresponding to one or more key process indicators (KPIs) and one or more cubelets divided along at least one of the one or more adjustable display dimensions. Embodiments display the mixed-reality object on the display, and adjust at least one of the one or more adjustable display dimensions in response to receiving a first input to the one or more sensors. In response to a second input, embodiments transform the one or more cubelets of the first cuboid.

Abstract: A system and method are disclosed associated with a cloud platform as a service provider. A monitoring agent, associated with a database service instance running on a client database virtual machine, periodically executes a performance throttling detection engine. The performance throttling detection engine gathers database statistics based on metrics and features of the database service using a rule-based approach. When it is determined that a pre-determined condition is met, the system may transmit the gathered database statistics to an external application. For example, the external application might comprise a database tuning service and the pre-determined condition may be associated with a decision that the database service may potentially need to tune knob configuration parameters (associated with memory knobs, background writer knobs, asynchronous knobs, etc.).