5 results about "Extensible architecture" patented technology

The invention provides a multi-level tenant management method. A tree-shaped hierarchical structure with a root tenant as a vertex is constructed, dynamic association of sub-tenants and automatic increasing of hierarchical depth values are realized by utilizing parent tenant identifiers, and a depth-extensible architecture is constructed as required. The root tenant independently configures the function permission and the resource permission for each sub-tenant, and a rigid mechanism depending on a static strategy table or a fixed permission distribution mode is replaced. Meanwhile, by binding an attribution tenant identifier for a system resource and clearly distinguishing the resource attribute as a private resource or a controllable resource, dual verification based on a hierarchical relationship and the resource attribute can be carried out, a resource boundary between tenants is implemented at a resource access source, the risk of data leakage caused by no isolation of a shared storage pool mode is solved, and the system performance is improved. And the problem of low efficiency caused by manual configuration required by cross-level collaboration in a physical resource direct binding mode is solved, so that efficient and safe resource collaboration operation within an authorization range is supported while data security isolation is guaranteed.

The application discloses an extensible architecture power distribution cabinet and relates to the technical field of power distribution cabinets. The power distribution cabinet comprises a bottom plate and a top plate, front, rear, left and right side plates are arranged between the bottom plate and the top plate, connecting assemblies are arranged on the bottom plate and the top plate, upper and lower extension plates are arranged on the connecting assemblies, four upper clamping grooves are arranged on the upper extension plate, and a lower clamping groove is arranged on the lower extension plate; upper clamping blocks are fixedly installed on the upper end faces of the front, rear, left and right side plates, lower clamping blocks are fixedly installed on the lower end faces of the front, rear, left and right side plates, and extension assemblies are arranged on the front, rear, left and right side plates. The power distribution cabinet is modularized, flexible adjustment and stability enhancement are achieved through cooperation of the extension assembly, the connecting assembly and the stability assembly, the performance, stability and use efficiency of the power distribution cabinet are remarkably improved, and the use effect of the power distribution cabinet is effectively improved.

The invention relates to a scalable architecture for automatically generating content distribution images. A method and system for automatically generating a content distribution image includes receiving a user input corresponding to a content distribution operation. The user input may be parsed to identify a keyword. Image data corresponding to the keyword may be identified. An image processing operation may be performed on the image data. A generative adversarial network is performed on the processed image data, including performing a first neural network on the processed image data to generate a first image corresponding to the keyword, the first image generated based on a likelihood that each of the first images is not detected to have been generated by the first neural network. The user interface may display a first image and a second image including an image previously being part of a content distribution operation or an image designated by an entity as available for the content distribution operation.

Methods and systems are presented for classifying a digital image of a document using a machine learning model framework. The machine learning model framework is configured to provide a classification output based on a fusion of features corresponding to different modalities and extracted from the digital image. The machine learning model framework includes multiple encoders. Each encoder is configured to encode features corresponding to a distinct modality into a respective embedding. Different embeddings generated by the multiple encoders are fused together using one or more fusion techniques. The fused embedding is provided to a machine learning model for classifying the document.

Methods and systems for automatically generating content distribution images are disclosed, including receiving user input corresponding to a content distribution operation. The user input can be parsed to identify a keyword. Image data corresponding to the keyword can be identified. Image processing operations can be performed on the image data. A generative adversarial network is performed on the processed image data, including performing a first neural network on the processed image data to generate first images corresponding to the keyword, the first images being generated based on a likelihood that each image in the first images is not detected as having been generated by the first neural network. A user interface can display the first images and a second image, the second image including an image that was previously part of the content distribution operation or an image specified by an entity as being available for the content distribution operation.