Abstract: A computer-implemented method for training an encoder. The encoder is configured for determining a latent representation of an image. Training the encoder includes: determining a latent representation and a noise image by providing a training image to the encoder, wherein the encoder is configured for determining a latent representation and a noise image for a provided image; masking out parts of the noise image, thereby determining a masked noise image; determining a predicted image by providing the latent representation and the masked noise image to a generator of a generative adversarial network; training the encoder by adapting parameters of the encoder based on a loss value, wherein the loss value characterizes a difference between the predicted image and the training image.

Abstract: Methods, systems, and devices for wireless communications are described. A communication device, otherwise known as a user equipment (UE) may determine a beam configuration associated with a set of directional beams of a base station. The beam configuration may include a set of identifiers associated with the set of directional beams. The UE may determine beam position information associated with a coverage area of each directional beam of the set of directional beams based on the beam configuration. Additionally or alternatively, the UE may determine beam classification information associated with the coverage area of each directional beam of the set of directional beams based on the beam configuration. The UE may select a directional beam of the set of directional beams based on the beam position information and the beam classification information, and communicate with the base station using the selected directional beam.

Abstract: An embodiment includes establishing, by a system, a knowledge base comprising a set of nodes, each node in the set of nodes representing an entity extracted from a dataset received by the system, where at least two nodes have a hierarchical relationship. The embodiment includes creating a node in the knowledge base according to a familiarity metric, the familiarity metric based on traversing the set of nodes of the knowledge base. The embodiment includes generating a prediction metric for a user of the system for each node of the knowledge base where the prediction metric is generated based in part on an ancestor node where the ancestor node preexists in the knowledge base. The embodiment also includes adjusting the prediction metric based on feedback of the user where the prediction metric predicts understanding of the entity of the dataset by the user.

Abstract: A computer-implemented method for ascertaining at least one systematic error during the classification of images into at least one image category by a classification algorithm. The method includes: providing a list of image features and respective value indications for each of the image features; applying combinatorial testing to ascertain a predetermined sequence of test cases, which each include a subcombination of the image features and/or value indications included in the list; generating at least one image file using a text-into-image generation algorithm, the file including a synthetic image assigned to the predetermined image category and has the image feature and the value indication; classifying the generated, synthetic image by means of the classification algorithm into at least one of the plurality of image categories; and ascertaining the misclassification value by comparing the image category classified by the classification algorithm with the predetermined image category.

Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for radar target tracking based on return signal strength. A wireless device, such as a radar device, may measure a received signal strength of a detected signal. The received signal strength may be associated with at least one bin of a radar image. The wireless device may compare the received signal strength to a filtered signal strength. The filtered signal strength may be associated with a threshold difference in signal strength from the filtered signal strength. The wireless device may track the at least one bin of the radar image in response to the received signal strength being less than or equal to the threshold difference in signal strength from the filtered signal strength.

Abstract: Mechanisms are provided for a user equipment (UE) to determine a transmission frequency or a time advance for an uplink transmission from the UE to a base station in a non-terrestrial wireless network (NTN) without global navigation satellite systems (GNSS) information available to the UE. A communication connection between the UE and a base station can be established. The UE can determine that GNSS information is not available, and report to the base station that the GNSS information is not available. The UE can receive, from the base station, an indication of one or more parameters for an uplink transmission from the UE to synchronize the uplink transmission. The UE can determine, based on a current transmission frequency and the received indication of the one or more parameters, a next transmission frequency and transmit the uplink transmission at the determined next transmission frequency.

Abstract: A device and a computer implemented method for determining at least one slice of a set of digital images on which a model for detecting an object in a digital image underperforms. Digital images are grouped into slices depending on embedding vectors that are determined for a respective patch that is determined for the respective digital images and depending on target values that are assigned to the respective embedding vector.

Abstract: The freshness of one or more terms in a documentation, indicative of a currency of the one or more terms is computed. Each term includes one or more constituent words, and the terms are visually marked as current or out-of-date based on the computed freshness. Upon marking a term as out-of-date, a latest term for the out-of-date term is retrieved or a most possible latest term for the out-of-date term is predicted.

Abstract: A user equipment (UE) is configured to receive physical downlink control channel (PDCCH) configuration information comprising repetitions for PDCCH candidates that comprise Downlink Control Information (DCI), receive PDCCH candidates and decode the PDCCH candidates based on the PDCCH configuration information. A UE is configured to receive semi-persistent scheduling (SPS) configuration information for a physical downlink shared channel (PDSCH), receive a PDSCH comprising Downlink Control Information (DCI) and decode the PDSCH comprising the DCI based on the SPS configuration information.

Abstract: A plasma-exclusion-zone ring for a substrate processing system includes a ring-shaped body with an upper portion and a base. The upper portion of the ring-shaped body defines an innermost radial surface and an uppermost surface. The base of the ring-shaped body defines: a radially outermost surface; a first bottom surface extending radially inward from the radially outermost surface; a second bottom surface extending radially inward from the first bottom surface; and a plasma-exclusion-zone ring notch i) extending radially inward from the radially outermost surface, ii) extending inward from a portion of the first bottom surface, and iii) recessed inward from the radially outermost surface and the first bottom surface. The first bottom surface extends at an acute angle from the second bottom surface.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may identify a beam used for communicating with a network entity, the beam associated with multiple bandwidth parts (BWPs) including a reference BWP with a first frequency. The UE may receive a BWP configuration from the network entity, the BWP configuration based on changing a frequency for at least one BWP of the multiple BWPs form the first frequency to a second frequency. Additionally or alternatively, the UE may identify a timing threshold associated with a BWP switching operation for multiple BWPs associated with the beam. The UE may switch from the first BWP to a second BWP during the timing threshold. The UE may communicate with the network entity according to the BWP configuration or the second BWP.

Abstract: A computer-implemented method of predicting a next token given a sequence of tokens by a transformer-based machine learning system. The method includes: processing an embedding of the sequence of tokens through multiple layers; determining a confidence score for individual tokens at a layer's output by multiplying the layer's output embedding with a weight matrix; at a predetermined pth layer, determining the K most likely next tokens; creating a pruned weight matrix by removing rows corresponding to other tokens; for predefined subsequent layers, determining a confidence score for only the K tokens using the pruned weight matrix; and returning the token with the highest confidence score exceeding a layer-specific threshold.

Abstract: Several designs of a gas distribution device for a substrate processing system are provided. The gas distribution device includes a dual plenum showerhead. Additionally, designs for a light blocking structure used with the showerheads are also provided.

Abstract: Embodiments of the present disclosure provide a video capturing method, a device, a storage medium, a computer program product and a computer program. The method comprises: when obtaining a target video by means of a segmented image-capturing mode, in response to an image-capture pause operation, controlling image-capturing to pause and obtaining at least one image-captured video segment corresponding to the target video, and displaying, in an image-capture interface, at least one video segment identification corresponding to the at least one image-captured video segment; and in response to a triggering operation on any one video segment identification among the at least one video segment identification, displaying a preview interface, and playing back, in the preview interface, an image-captured video segment corresponding to the any one video segment identification.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive system information associated with a set of neighboring cells included in a non-terrestrial network (NTN). The UE may be connected to or camped in a current cell included in the NTN. The current cell may be associated with a current platform. The UE may monitor a neighboring cell, of the set of neighboring cells, based at least in part on the system information. Numerous other aspects are provided.

Abstract: A computer-implemented method and system for generating a dataset for training and/or validating a first machine learning algorithm. The method includes: providing an input dataset comprising a set of images, wherein objects to be classified are depicted on the images, wherein each image is assigned to at least one class having a class label; for each image, generating a crop of the image, wherein the crop includes the object to be classified; inputting the image and the generated crop into a second machine learning algorithm; generating a label for the crop; providing a dataset including the set of images, wherein each image is assigned the respectively generated label.

Abstract: A device, a datastructure, and a computer implemented method for digital content processing. The method includes providing a first dataset; providing a second dataset; wherein a digital content of a respective element of the elements of the first and second datasets include a digital image or a digital audio signal; generating, with a data-to-text model, a first set of descriptions, wherein the first set comprises an element-wise description of the elements of the first dataset, wherein the description of the respective element of the first dataset is determined depending on the content of the respective element of the first dataset; generating, with the data-to-text model, a second set of descriptions, wherein the second set comprises an element-wise description of the elements of the second dataset, wherein the description of the respective element of the second dataset is determined depending on the content of the respective element of the second dataset.

Abstract: Detecting fine-grained similarity in image includes determining a core area of a search image by generating an image salient map from a plurality of layers of the search image and determining a connected area based on the image salient map. Feature descriptors are generated from the core area of the search image. A plurality of capsule vectors are generated from different ones of a plurality of keypoints of the feature descriptors. Capsule vectors of the search image are compared with capsule vectors of each image of the dataset to generate a top-K matrix. Similarity scores for the top-K matrix are calculated. One or more image of the dataset having fine-grained similarity with the search image are selected based a bundled similarity score for each image of the dataset. The bundled similarity score is a summation of the similarity scores of the image.

Abstract: A plasma-exclusion-zone ring for a substrate processing system that is configured to process a substrate includes a ring-shaped body, an upper portion of the ring-shaped body, a base and a plasma-exclusion-zone ring notch. The upper portion of the ring-shaped body defines a radially inner surface and a top surface. The base of the ring-shaped body defines a radially outer surface, a first bottom surface extending radially inward from the radially outer surface, and a second bottom surface extending radially inward from the first bottom surface. The plasma-exclusion-zone ring notch is proportional to an alignment notch of the substrate. The first bottom surface is tapered and extends at an acute angle from the second bottom surface to the radially outer surface. The first bottom surface is configured to extend over and oppose a periphery of the substrate.