Abstract: A filtration article having a honeycomb filter body that includes a plurality of intersecting porous walls including surfaces that define a plurality of channels extending in a longitudinal direction from an inlet end to an outlet end. The plurality of channels includes inlet channels that are open at the inlet end and sealed at locations longitudinally spaced away from the inlet end, and outlet channels that are open at the outlet end and sealed at locations longitudinally spaced away from the outlet end. Inorganic deposits are disposed on, or in, or both on and in, at least some of the walls. The inorganic deposits are bound to each other, to the walls, or to both, by a silicon-containing precursor binder.

Abstract: Filtration articles herein exhibit excellent filtration efficiency and pressure drop before and after water durability testing. The articles comprise: a honeycomb filter body; inorganic deposits disposed within the honeycomb filter body at a loading of less than or equal to 20 grams of the inorganic deposits per liter of the honeycomb filter body. The inorganic deposits are comprised of refractory inorganic nanoparticles bound by a high temperature binder comprising one or more inorganic components. At least a portion of the inorganic deposits form a porous inorganic network over portions of inlet walls of the honeycomb filter body.

Abstract: Aspects for machine learning-based link adaptation are described. For example, an apparatus can determine k-nearest neighbors (K-NNs) based on training data associated with the sub-band and on the signal to interference and noise ratio (SINR) of the sub-band. In aspects, the apparatus can identify a channel quality indicator (CQI) associated with the lowest error rate for the k-NNs and provide the identified CQI to a base station. In aspects, a neural network (NN) can provide labels for CQIs that indicate probability of choosing a CQI, and the CQI having highest probability will be provided to a base station. In aspects, a covariance matrix based on samples of a communication channel can be provided to a NN to determine a rank indicator (RI) corresponding to the channel, and channel state information associated with the (RI) can be sent to the base station. Other aspects are described.

Abstract: Techniques related to convolutional neural network based loop filtering for video coding are discussed and include training a convolutional neural network loop filter for each of multiple classifications into which each region of a reconstructed video frame corresponding to input video are classified and selecting a subset of the trained convolutional neural network loop filter for use in coding the input video.

Abstract: A method, system, medium, and article provide neural network loop filtering for video coding with multiple alternative neural networks.

Abstract: Devices and methods for determining a Modulation and Coding Scheme (MCS) index to provide in a feedback to a network, including providing a plurality of inputs, wherein a first subset of the plurality of inputs includes one or more resource block inputs each corresponding to a resource block from a post-signal-to-interference-noise-ratio (post-SINR), and wherein a second subset of the plurality of inputs includes MCS information; determining a plurality of outputs based on the plurality of inputs, wherein each of the plurality of outputs corresponds to a respective MCS index; and selecting an MCS index from the plurality of outputs to provide in the feedback to the network.

Abstract: Filtration articles herein exhibit excellent filtration efficiency and pressure drop before and after water durability testing. The articles comprise: a honeycomb filter body; inorganic deposits disposed within the honeycomb filter body at a loading of less than or equal to 20 grams of the inorganic deposits per liter of the honeycomb filter body. The inorganic deposits are comprised of refractory inorganic nanoparticles bound by a high temperature binder comprising one or more inorganic components. At least a portion of the inorganic deposits form a porous inorganic network over portions of inlet walls of the honeycomb filter body.

Abstract: A method, system, medium, and article provide neural network loop filtering for video coding with multiple alternative neural networks.

Abstract: Aspects for machine learning-based link adaptation are described. For example, an apparatus can determine k-nearest neighbors (K-NNs) based on training data associated with the sub-band and on the signal to interference and noise ratio (SINR) of the sub-band. In aspects, the apparatus can identify a channel quality indicator (CQI) associated with the lowest error rate for the k-NNs and provide the identified CQI to a base station. In aspects, a neural network (NN) can provide labels for CQIs that indicate probability of choosing a CQI, and the CQI having highest probability will be provided to a base station. In aspects, a covariance matrix based on samples of a communication channel can be provided to a NN to determine a rank indicator (RI) corresponding to the channel, and channel state information associated with the (RI) can be sent to the base station. Other aspects are described.

Abstract: A method, system, medium, and article provide neural network loop filtering for video coding with multiple alternative neural networks.

Abstract: Methods, apparatus, systems, and articles of manufacture for image compression using autoencoder information are disclosed. An example apparatus disclosed herein includes a pre-compressor to compress an input scaled image to generate a fundamental bitstream and a reconstructed scaled image. The disclosed example apparatus also includes an autoencoder to encode a residual of a reconstructed image to generate a side information bitstream, the reconstructed image based on the reconstructed scaled image. The disclosed example apparatus further includes a bitstream merger to combine the fundamental bitstream and the side information bitstream to generate an output compressed bitstream.

Abstract: A method, system, medium, and article provide neural network loop filtering for video coding with multiple alternative neural networks.