Abstract: A display device includes a diffusion layer providing a single well, an optical element configured to receive light and output the received image light including a concentric series of lens segments made up of active facets, and a waveguide having an in-coupling grating and a waveguide body optically coupled to the image light, where a polarizing component is disposed over an output surface of the optical element. A method to improve a yield of silicon backplane displays includes connecting a diode having a resolution to a backplane and repairing a defect on a pixel display area by dividing the pixel display area into at least one subcircuit, while improving geometry stylization transfer for 3D models of real-world environments. A method for suppressing crosstalk for user conversations includes receiving multiple speech signals captured by multiple microphones and generating directional data for the multiple speech signals based on spatial filtering.

Abstract: In one embodiment, a method by a computing system associated with an image sensor including a quad-Bayer color filter array includes accessing image-sensor data generated by the image sensor, where the quad-Bayer color filter array comprises sixteen sets of filters, each corresponding to a pixel location within a quad-Bayer pattern, splitting the image-sensor data into sixteen packed channels, where each of the sixteen packed channels corresponds to one of the sixteen sets of filters, producing three channels of interpolated pixels by processing the sixteen packed channels using a machine-learning model, where the three channels comprise red, green, and blue channels, and constructing an output image using the three channels of the interpolated pixels.

Abstract: A holographic calling system can capture and encode holographic data at a sender-side of a holographic calling pipeline and decode and present the holographic data as a 3D representation of a sender at a receiver-side of the holographic calling pipeline. The holographic calling pipeline can include stages to capture audio, color images, and depth images; densify the depth images to have a depth value for each pixel while generating parts masks and a body model; use the masks to segment the images into parts needed for hologram generation; convert depth images into a 3D mesh; paint the 3D mesh with color data; perform torso disocclusion; perform face reconstruction; and perform audio synchronization. In various implementations, different of these stages can be performed sender-side or receiver side. The holographic calling pipeline also includes sender-side compression, transmission over a communication channel, and receiver-side decompression and hologram output.

Abstract: A method, a user equipment, UE, a network node, and a computer program product for classifying channel state information, CSI, compression quality in a wireless communication network are provided. The method is performed in a UE in the wireless communication network. The method includes obtaining CSI associated with one or more radio channels. Further, the method includes compressing the CSI into an encoded format representing a compressed CSI. The method further includes classifying a CSI compression quality related to reconstruction of the one or more radio channels of the compressed CSI using a classifier predicting a resulting performance loss associated with the reconstruction of the one or more radio channels. The classification of the CSI compression quality is based on a level of predicted performance loss.

Abstract: Embodiments include methods for a radio access network (RAN) node configured to serve one or more user equipment (UEs). Such methods include transmitting reference signals (RS) for a downlink (DL) channel and receiving, from a UE, a report including encoded feedback representing the DL channel. The encoded feedback comprises a UE DL channel estimate mapped to a channel feature set based on a first mapping that is proprietary to the UE. The channel feature set is compressed based on a second mapping that is known by the UE and the RAN node. Such methods also include, using a decoder function of a neural-network autoencoder (NNAE), decoding the encoded feedback to obtain a reconstruction of the channel feature set. Other embodiments include complementary methods for a UE, as well as RAN nodes and UEs configured to perform such methods.

Abstract: Embodiments include methods for a radio access network (RAN) node. Such methods include transmitting downlink (DL) reference signals (RS) in accordance with one or more configurations and receiving, from each of one or more user equipment (UEs), feedback representing a DL channel from the RAN node to the UE. The feedback is based on the UE's measurements of the transmitted DL RS and is encoded by one or more UE encoders that correspond to respective RAN node decoders. Such methods include, for each of the one or more UEs, obtaining one or more measurements of uplink (UL) RS transmitted by the UE in accordance with the one or more configurations. Such methods include training the RAN node decoder(s) based on the received feedback and the obtained UL RS measurements. Other embodiments include complementary methods for UEs, as well as RAN nodes and UEs configured to perform such methods.

Abstract: According to an aspect, there is provided a method of training an autoencoder in a target domain. The autoencoder includes a first neural network encoder for use in a wireless device and a first neural network decoder for use in a base station. The method includes: obtaining a first set of weights; training a second neural network encoder in a source domain using a first data set to determine a first set of weights, wherein the second neural network encoder has the same structure as the first neural network encoder; setting weights of the first neural network encoder to the first set of weights; and training the first neural network decoder using a second data set, during which the weights of the first neural network encoder are fixed.

Abstract: A vaporization system and control method are provided. Liquid cryogen is provided to first ambient air vaporizer (AAV) units. When an output superheated vapor temperature is less than a threshold, the liquid cryogen is provided to second AAV units. When greater than or equal to the threshold, it is determined whether the second AAV units are defrosted. When defrosted, the liquid cryogen is provided to the second AAV units. When not defrosted, it is determined whether ice has formed on the first AAV units. When not formed, it is again determined whether the superheated vapor temperature is less than the threshold. When formed, it is determined whether a current ambient condition is favorable to defrosting the second AAV units. When not favorable, the liquid cryogen is provided to the second bank of AAV units. When favorable, it is again determined whether the superheated vapor temperature is less than the threshold.

Abstract: A method for a building management system includes detecting a fault from timeseries building data, classifying a time period of the timeseries building data as a faulty time period based on the fault, and playing an audiovisual presentation of the fault and the timeseries building data by visually advancing through the timeseries building data in a chronological order and emitting a tone when the timeseries building data for the faulty time period is presented.

Abstract: In one embodiment, a method includes accessing a video captured by cameras which is associated with a first framerate lower than a threshold framerate, for any two adjacent frames of the accessed video: generating a warped frame from the two adjacent frames based on an optical flow associated with the two adjacent frames, determining alignments for the two adjacent frames, respectively, fusing the determined alignments for the two adjacent frames, and generating a reconstructed frame based on the fused alignment, and reconstructing the accessed video based on the any two adjacent frames and their respective reconstructed frames, wherein the reconstructed video is associated with a second framerate higher than the threshold framerate.

Abstract: In one embodiment, a method includes accessing a sequence of raw images comprising at least a first raw image, a second raw image, and a third raw image sequentially, wherein the second raw image comprises image noise, warping the first and third raw images with respect to the second raw image based on an optical flow associated with the sequence of raw images, generating an input tensor based on the first warped raw image, the second raw image, and the third warped raw image, and generating a denoised raw image based on one or more machine-learning models for the second raw image based on the input tensor.

Abstract: Methods, systems, and apparatuses for discovering dynamic path maximum transmission unit (PMTU) between a sending computing device and a receiving computing device (e.g., a client device and a host device) are described herein. A sending computing device may iteratively transmit bursts of probe packets, each burst being defined by a search range between a maximum packet size and a minimum packet size. The sending computing device may iteratively update the search range based on the previous iteration until the search converges on the PMTU. When the PMTU is discovered, each of the computing devices may update their transport and presentation layer buffers based on the discovered PMTU without any other protocol level disruption. In a multi-path scenario, the computing device may discover PMTU for each of the paths and select a performance optimal path based on the individual PMTUs and other network characteristics such as loss, latency, and throughput.

Abstract: A holographic calling system can capture and encode holographic data at a sender-side of a holographic calling pipeline and decode and present the holographic data as a 3D representation of a sender at a receiver-side of the holographic calling pipeline. The holographic calling pipeline can include stages to capture audio, color images, and depth images; densify the depth images to have a depth value for each pixel while generating parts masks and a body model; use the masks to segment the images into parts needed for hologram generation; convert depth images into a 3D mesh; paint the 3D mesh with color data; perform torso disocclusion; perform face reconstruction; and perform audio synchronization. In various implementations, different of these stages can be performed sender-side or receiver side. The holographic calling pipeline also includes sender-side compression, transmission over a communication channel, and receiver-side decompression and hologram output.

Abstract: A holographic calling system can capture and encode holographic data at a sender-side of a holographic calling pipeline and decode and present the holographic data as a 3D representation of a sender at a receiver-side of the holographic calling pipeline. The holographic calling pipeline can include stages to capture audio, color images, and depth images; densify the depth images to have a depth value for each pixel while generating parts masks and a body model; use the masks to segment the images into parts needed for hologram generation; convert depth images into a 3D mesh; paint the 3D mesh with color data; perform torso disocclusion; perform face reconstruction; and perform audio synchronization. In various implementations, different of these stages can be performed sender-side or receiver side. The holographic calling pipeline also includes sender-side compression, transmission over a communication channel, and receiver-side decompression and hologram output.

Abstract: An approach is provided in which the approach trains a machine learning model using reference entries included in a reference dataset. During the training, the machine learning model learns a first set of unidirectional associations between the reference entries. The approach inputs a user dataset into the trained machine learning model and generates a second set of unidirectional associations between user dataset entries included in the user dataset. The approach builds a hierarchical relationship of the user dataset based on the second set of unidirectional associations and manages the user dataset based on the hierarchical relationship.

Abstract: A method and a network agent for providing cell assignment for a wireless device served by a network node. An input vector is created for a set of candidate cells based on measurements by the wireless device and/or by the network node related to performance and signals. A future effect of assigning the wireless device to a candidate cell is estimated for each candidate cell by applying the created input vector to an effect estimation function which may be a Q-learning function. A cell in the set of candidate cells is then determined and assigned for the wireless device, based on the estimated future effects of the candidate cells. The cell that provides the best future effect may be selected for cell assignment.

Abstract: Methods, systems, and apparatuses for discovering dynamic path maximum transmission unit (PMTU) between a sending computing device and a receiving computing device (e.g., a client device and a host device) are described herein. A sending computing device may iteratively transmit bursts of probe packets, each burst being defined by a search range between a maximum packet size and a minimum packet size. The sending computing device may iteratively update the search range based on the previous iteration until the search converges on the PMTU. When the PMTU is discovered, each of the computing devices may update their transport and presentation layer buffers based on the discovered PMTU without any other protocol level disruption. In a multi-path scenario, the computing device may discover PMTU for each of the paths and select a performance optimal path based on the individual PMTUs and other network characteristics such as loss, latency, and throughput.

Abstract: The present invention generally relates to a self-charging system for electric vehicles comprises at least one gearbox comprises an input end and an output end mechanically coupled to one of the wheels of a vehicle to the input end to generate a rotational energy with an increased output of one of the torque or speed (RPM) to the output end; an auxiliary generator connected to the output end of the at least one gearbox to convert the rotational energy into electrical energy; a controller equipped with a maximum power point tracker to produce maximum power output; and a charger controller coupled to the maximum power point tracker to charge a batter of the vehicle upon limiting electric current rate of the power output to protect against electrical overload, overcharging, and overvoltage.

Abstract: Methods, systems, and apparatuses for discovering dynamic path maximum transmission unit (PMTU) between a sending computing device and a receiving computing device (e.g., a client device and a host device) are described herein. A sending computing device may iteratively transmit bursts of probe packets, each burst being defined by a search range between a maximum packet size and a minimum packet size. The sending computing device may iteratively update the search range based on the previous iteration until the search converges on the PMTU. When the PMTU is discovered, each of the computing devices may update their transport and presentation layer buffers based on the discovered PMTU without any other protocol level disruption. In a multi-path scenario, the computing device may discover PMTU for each of the paths and select a performance optimal path based on the individual PMTUs and other network characteristics such as loss, latency, and throughput.

Abstract: A holographic calling system can capture and encode holographic data at a sender-side of a holographic calling pipeline and decode and present the holographic data as a 3D representation of a sender at a receiver-side of the holographic calling pipeline. The holographic calling pipeline can include stages to capture audio, color images, and depth images; densify the depth images to have a depth value for each pixel while generating parts masks and a body model; use the masks to segment the images into parts needed for hologram generation; convert depth images into a 3D mesh; paint the 3D mesh with color data; perform torso disocclusion; perform face reconstruction; and perform audio synchronization. In various implementations, different of these stages can be performed sender-side or receiver side. The holographic calling pipeline also includes sender-side compression, transmission over a communication channel, and receiver-side decompression and hologram output.