Abstract: A computer-implemented method of detecting anomalies in sensor measurements of a physical quantity. Measurement data is obtained including multiple sensor measurements of the physical quantity. Respective weights are determined for respective sensor measurements by maximizing a discrepancy between the measurement data and a mixture distribution obtained by reweighting the sensor measurements according to the weights. The respective weights are output as indicators of outlier likelihoods for the respective sensor measurements.

Abstract: A multi-framework blockchain service may be implemented with a common interface to manage different types of blockchain networks. Requests to create a blockchain network may be received via an interface for the control plane that triggers the creation of the blockchain network according to an identified workflow. Various operations to change the blockchain network, including membership changes, node additions, governance changes, analytics changes, and monitoring changes may be allowed or denied by the control plane according to a distributed governance policy in effect for the blockchain network.

Abstract: A method is provided for training a selective network that includes a selection node for selecting whether to make a prediction. During training, the selection node is reparameterized as a differentiable function of learnable parameters acting on noise from a base distribution. The differentiable function approximates a sampling from a categorical distribution.

Abstract: The typical service to deliver multimedia content is evolved Multimedia Broadcast Multicast Service (eMBMS). However, the eMBMS is a service-oriented network architecture requiring a pre-defined and pre-established user service to stream a live video. The content provider must be a multicast service provider to use the eMBMS services, which many typical content providers are not. Accordingly, the present disclosure provides a live video streaming network architecture that enhances the eMBMS architecture to enable service-less multicast delivery. The provided system includes a virtual network function service running on an application server (AS) that identifies potential multicast scenarios based on user requests for a live video stream within a confined area.

Abstract: Real-time scene understanding system employing an object detection module with an algorithm for localization and classification of objects in an image, and a semantic segmentation module with an algorithm for classification of individual pixels in the image, wherein the system comprises an encoder module operable on an input image for the extraction of notable features in the input image, one or more attention modules to attribute among the notable features in the input image as provided by the encoder a relative contribution of each of such notable features in an output image to be reconstructed from the input image, and a decoder module for reconstructing the output image using the notable features, wherein the reconstructed output image is made available to the object detection module with the algorithm for localization and classification of objects in the image, and to the semantic segmentation module with the algorithm for classification of individual pixels in the image.

Abstract: The typical service to deliver multimedia content is evolved Multimedia Broadcast Multicast Service (eMBMS). However, the eMBMS is a service-oriented network architecture requiring a pre-defined and pre-established user service to stream a live video. The content provider must be a multicast service provider to use the eMBMS services, which many typical content providers are not. Accordingly, the present disclosure provides a live video streaming network architecture that enhances the eMBMS architecture to enable service-less multicast delivery. The provided system includes a virtual network function service running on an application server (AS) that identifies potential multicast scenarios based on user requests for a live video stream within a confined area.

Abstract: Real-time scene understanding system employing an object detection module with an algorithm for localization and classification of objects in an image, and a semantic segmentation module with an algorithm for classification of individual pixels in the image, wherein the system comprises an encoder module operable on an input image for the extraction of notable features in the input image, one or more attention modules to attribute among the notable features in the input image as provided by the encoder a relative contribution of each of such notable features in an output image to be reconstructed from the input image, and a decoder module for reconstructing the output image using the notable features, wherein the reconstructed output image is made available to the object detection module with the algorithm for localization and classification of objects in the image, and to the semantic segmentation module with the algorithm for classification of individual pixels in the image.

Abstract: A multi-framework blockchain service may be implemented with a common interface to manage different types of blockchain networks. Requests to create a blockchain network may be received via an interface for the control plane that triggers the creation of the blockchain network according to an identified workflow. Various operations to change the blockchain network, including membership changes, node additions, governance changes, analytics changes, and monitoring changes may be allowed or denied by the control plane according to a distributed governance policy in effect for the blockchain network.