Abstract: A cognitive learning method comprising: monitoring a user interaction of a user; generating user interaction data based upon the user interaction; receiving data from a plurality of data sources; processing the user interaction data and the data from the plurality of data sources to perform a cognitive learning operation, the processing being performed via a cognitive inference and learning system, the cognitive learning operation comprising analyzing the user interaction data, the cognitive learning operation generating a cognitive learning result based upon the user interaction data; and, associating a cognitive profile with the user based the cognitive learning result.

Abstract: A device may determine whether to enable or disable bi-directional optical flow (BIO) for a current coding unit (CU) (e.g., block and/or sub-block). Prediction information for the CU may be identified and may include prediction signals associated with a first reference block and a second reference block (e.g., or a first reference sub-block and a second reference sub-block). A prediction difference may be calculated and may be used to determine the similarity between the two prediction signals. The CU may be reconstructed based on the similarity. For example, whether to reconstruct the CU with BIO enabled or BIO disabled may be based on whether the two prediction signals are similar, it may be determined to enable BIO for the CU when the two prediction signals are determined to be dissimilar. For example, the CU may be reconstructed with BIO disabled when the two prediction signals are determined to be similar.

Abstract: A cognitive information processing system environment comprising: a plurality of data sources, at least some of the plurality of data sources comprising healthcare relevant data sources; a cognitive inference and learning system coupled to receive a data from the plurality of data sources, the cognitive inference and learning system processing the data from the plurality of data sources to provide cognitively processed healthcare relevant insights, the cognitive inference and learning system further comprising performing a learning operation to iteratively improve the cognitively processed healthcare relevant insights over time; and, a destination, the destination receiving the cognitively processed healthcare relevant insights.

Abstract: A computer-implementable method for ingesting information into a cognitive graph comprising: receiving data from a data source; determining whether the data comprises text; processing the data, the processing comprising performing a natural language processing operation on the data, the processing the data identifying a plurality of knowledge elements based upon the natural language processing operation; and, storing at least some of the knowledge elements within the cognitive graph as a collection of knowledge elements, the storing universally representing knowledge obtained from the data.

Abstract: A computer-implementable method for managing a cognitive graph comprising: receiving data from a data source; determining whether the data comprises text; processing the data, the processing comprising performing a parsing operation on the data, the processing the data identifying a plurality of knowledge elements based upon the parsing operation; and, storing the knowledge elements within the cognitive graph as a collection of knowledge elements, the storing universally representing knowledge obtained from the data.

Abstract: A video device may generate an enhanced inter-layer reference (E-ILR) picture io assist in predicting an enhancement layer picture of a. scalable bitstream. An E-ILR picture may include one or more E-ILR blocks. An E-ILR block may be generated using a differential method, a residual method, a bi-prediction method, and/or a uni-prediction method. The video device may determine a first time instance. The video device may subtract a block of a first base layer picture characterized by the first time instance from a block of an enhancement layer picture characterized by the first time instance to generate a differential block characterized by the first time instance. The video device may perform motion compensation on the differential block and add the motion compensated differential picture to a block of the second base layer picture characterized by the second time instance to generate an E-ILR. block.

Abstract: A system comprising: a processor; a data bus coupled to the processor; and a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus. The computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for: receiving data from a data source; determining whether the data comprises text; processing the data, the processing comprising performing a lossless parsing operation on the data, the processing the data identifying a plurality of knowledge elements based upon the parsing operation; and, storing the knowledge elements within the cognitive graph as a collection of knowledge elements, the storing universally representing knowledge obtained from the data.

Abstract: Systems and methods are disclosed for improving the prediction efficiency for residual prediction using motion compensated residual prediction (MCRP). Exemplary residual prediction techniques employ motion compensated prediction and processed residual reference pictures. Further disclosed herein are systems and methods for generating residual reference pictures. These pictures can be generated adaptively with or without considering in-loop filtering effects. Exemplary de-noising filter designs are also described for enhancing the quality of residual reference pictures, and compression methods are described for reducing the storage size of reference pictures. Further disclosed herein are exemplary syntax designs for communicating residuals' motion information.

Abstract: Systems and methods for adaptively streaming video content to a wireless transmit/receive unit (WTRU) or wired transmit/receive unit may comprise obtaining a media presentation description that comprises a content authenticity, requesting a key for a hash-based message authentication code; receiving the key for the hash-based message authentication code, determining a determined hash for a segment of the media presentation description, requesting a reference hash for the segment from a server, receiving the reference hash for the segment from the server, and comparing the reference hash to the determined hash to determine whether the requested hash matches the determined hash.

Abstract: 360-degree video content may be coded. A sampling position in a projection format may be determined to code 360-degree video content. For example, a sampling position in a target projection format and a sampling position in a reference projection format may be identified. The sample position in the target projection format may be related to the corresponding sample position in the reference projection format via a transform function. A parameter weight (e.g., a reference parameter weight) for the sampling position in the reference projection format may be identified. An adjustment factor associated with the parameter weight for the sampling position in the reference projection format may be determined. The parameter weight (e.g., adjusted parameter weight) for the sampling position in the target projection format may be calculated. The calculated adjusted parameter weight may be applied to the sampling position in the target projection format when coding the 360-degree video content.

Abstract: Media content coded using scalable coding techniques may be cached among a group of cache devices. Layered segments of the media content may be pre-loaded onto the cache devices, which may be located throughout a content distribution network, including a home network. The caching location of the media content may be determined based on multiple factors including a content preference associated with the group of cache devices and device capabilities. A cache controller may manage the caching of the media content.

Abstract: Sampling grid information may be determined for multi-layer video coding systems. The sampling grid information may be used to align the video layers of a coding system. Sampling grid correction may be performed based on the sampling grid information. The sampling grids may also be detected. In some embodiments, a sampling grid precision may also be detected and/or signaled.

Abstract: Systems, methods, and instrumentalities are disclosed for inverse shaping for high dynamic range (HDR) video coding. A video coding device, e.g., such as a decoder, may determine a plurality of pivot points associated with a plurality of piecewise segments of an inverse reshaping model. The plurality of pivot points may be determined based on an indication received via a message. Each piecewise segment may be defined by a plurality of coefficients. The video coding device may receive an indication of a first subset of coefficients associated with the plurality of piecewise segments. The video coding device may calculate a second subset of coefficients based on the first subset of coefficients and the plurality of pivot points. The video coding device may generate an inverse reshaping model using one or more of the plurality of pivot points, the first subset of coefficients, and the second subset of coefficients.

Abstract: A method, system and computer readable medium for generating a cognitive insight comprising: receiving content element data, the content element data representing a content element, the content element comprising an element of a corpus of content; performing a cognitive learning operation on the content element data, the cognitive learning operation identifying descriptive information associated with the content element; associating a cognitive attribute with the content element using the descriptive information associated with the content element.

Abstract: Systems, methods, and instrumentalities are disclosed for a 360-degree video streaming. A video streaming device may receive a 360-degree video stream from a network node. The video streaming device may determine a viewport associated with the video streaming device and/or the 360-degree video stream. The video streaming device may determine (e.g., based on the viewport} to request in advance a first segment and a second segment of the 360-degree video stream. The video streaming device may determine a relative priority order for the first segment and the second segment. The video streaming device may generate an anticipated requests message. The anticipated requests message may indicate the determined relative priority order, for example, by listing the first segment and the second segment in decreasing relative priority based on the determined relative priority order. The video streaming device may send the anticipated requests message to the network node.

Abstract: A method, system and computer-usable medium for providing cognitive insights comprising receiving data from a plurality of data sources, the plurality of data sources comprising a blockchain data source, the blockchain data source providing blockchain data; processing the data from the plurality of data sources, the processing the data from the plurality of data sources performing data enriching to provide enriched data; generating the cognitive session graph, the cognitive session graph being associated with a session, the cognitive session graph comprising at least some enriched data; and, associating a cognitive blockchain with the cognitive session graph.

Abstract: A coding device (e.g., that may be or may include encoder and/or decoder) may receive a frame-packed picture of 380-degree video. The coding device may identify a face in the frame-packed picture that the current block belongs to. The coding device may determine that a current block is located at a boundary of the face that the current block belongs to. The coding device may identify multiple spherical neighboring blocks of the current block. The coding device may identify a cross-face boundary neighboring block. The coding device may identify a block in the frame-packed picture that corresponds to the cross-face boundary neighboring block. The coding device may determine whether to use the identified block to code the current block based on availability of the identified block. The coding device may code the current block based on the determination to use the identified block.

Abstract: A method, system and computer-usable medium for providing cognitive insights comprising receiving streams of data from a plurality of data sources; receiving data from a plurality of data sources, the plurality of data sources comprising a blockchain data source, the blockchain data source providing blockchain data; processing the data from the plurality of data sources, the processing the data from the plurality of data sources performing data enriching to provide enriched data; generating the cognitive session graph, the cognitive session graph being associated with a session, the cognitive session graph comprising at least some enriched data; and, associating a cognitive blockchain with the cognitive session graph.

Abstract: A data architecture for use within a cognitive information processing system environment comprising: a plurality of data sources, the plurality of data sources comprising a public data source and a private data source, the public source comprising a public blockchain data source, the private data source comprising a private blockchain data source; a cognitive data management module, the cognitive data management module accessing information from the plurality of data sources, the information comprising public blockchain information and private blockchain information; and, providing the information to a cognitive inference and learning system.

Abstract: A method for receiving a plurality of types of data within a cognitive information processing system environment comprising: receiving data from a plurality of data sources, the plurality of data sources comprising a public data source and a private data source the public source comprising a public blockchain data source, the private data source comprising a private blockchain data source; accessing information from the plurality of data sources via a cognitive data management module, the information comprising public blockchain information and private blockchain information; and, providing the information to an inference and learning system.