Abstract: A humidity reduction apparatus and a method for reducing the humidity of a volume of gas. The humidity reduction apparatus comprises a gas delivery conduit, at least one heat-conductive media positioned in-line within at least a portion of the gas delivery conduit, and a cooler in contact with at least a portion of the gas delivery conduit to cool the gas delivery conduit and the at least one heat-conductive media. The gas delivery conduit comprises at least one conducting portion. The first side of the cooler is configured to cool the at least one conducting portion of the gas delivery conduit and the at least one heat-conductive media. The voltage applied across the cooler is selectably reversed such that the first side heats the at least one conducting portion of the gas delivery conduit and the at least one heat-conductive media.

Abstract: Embodiments of the invention are directed to automatically capturing user interface screenshots for use in documentation of a software product. Aspects include identifying a user interface window of the software product and creating a degree-of-completion graph for the user interface window. Aspects also include capturing a plurality of screenshots of the user interface window during use of the software product and calculating a degree-of-completion percentage for each of the plurality of screenshots. Aspects further include identifying a subset of the plurality of screenshots to be included in the software product documentation based on the degree-of-completion percentage.

Abstract: Satellites in a non-terrestrial network may provide positioning reference signals (PRS) to user equipment (UE), with which the UE may determine its position using propagation delay difference measurements, such as Time Difference of Arrival (TDOA) measurement. Due to the large distances between satellites and the UE, the propagation delay differences in the PRS received from satellites may exceed half a radio frame, resulting in a frame level timing ambiguity in the differential measurements. The satellites transmit secondary PRS, along with primary PRS, that include timing information to resolve frame level timing ambiguity of the primary PRS. The positioning occasions in the secondary PRS, for example, may be aligned with corresponding positioning occasions primary PRS within each radio frame, and are transmitted with a periodicity that is an integer multiple (greater than 1) of that of the primary PRS to resolve the frame level timing ambiguity of the primary PRS.

Abstract: According to one embodiment, a method, computer system, and computer program product for adjusting an audible area of an avatar's voice is provided. The present invention may include receiving, at a microphone, a source audio; creating a received audio; calculating, by a generative model, a voice propagation distance of a user based on the source audio, the received audio, and a templated text sentence describing a category of a mixed reality environment experienced by the user; drawing a virtual circle within the mixed reality environment centered on a user avatar representing the user and with a radius equal to the voice propagation distance; and transmitting the source audio to one or more participants within the mixed-reality environment represented by one or more participant avatars located within the virtual circle.

Abstract: In an aspect for generating a 2-dimensional (2D) building mapping, a computer-implemented method may include one or more processors configured for receiving scanning data in a first file format corresponding to 3-dimensional (3D) aerial Light Detection and Ranging (LiDaR) images. Further, the method may include transforming the first file format to a second file format and transmitting the scanning data to a building semantic segmentation component. Further, the computer-implemented method may include generating semantic segmentation data corresponding to building structures defined by point clusters; generating instance segmentation data corresponding to top surfaces of the building structures; generating building boundary data for each one of the point clusters based on one or more of the semantic segmentation data and the instance segmentation data; and processing the building boundary data to generate a 2D building mapping comprising refined boundary lines for each of the point clusters.

Abstract: A method for measuring the ability of a trained machine learning model for the processing of measurement data to generalize, with respect to a given task, to a target domain and/or distribution to which one or more input records of measurement data belong. The method includes: determining), from the input records of measurement data, a target style that characterizes the target domain and/or distribution; obtaining, based at least in part on the target style, validation examples in the target domain and/or distribution, and also corresponding ground truth labels; processing, by the trained machine learning model, the validation examples into outputs; and determining, based on a comparison between the outputs and the respective ground truth labels, the accuracy of the trained machine learning model as the sought ability of the trained machine learning model to generalize to the target domain.

Abstract: A method for detecting whether a given input record of measurement data that is inputted to a trained machine learning model is in the domain and/or distribution of training examples with which the machine learning model was trained. The method includes: determining, from each training example, a training style that characterizes the domain and/or distribution to which the training example belongs; determining, from the given input record of measurement data, a test style that characterizes the domain and/or distribution to which the given record of measurement data belongs; evaluating, based on the training styles and the test style, to which extent the test style is a member of the distribution of the training styles; and based at least in part on the outcome of this evaluation, determining whether the given record of measurement data is in the domain and/or distribution of the training examples.

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: A device and a method for determining a class for at least a part of a digital image. The method includes: providing a classifier for a first class and a second class; determining a digital image including an object of the second class in at least the part of the digital image; determining the class for at least the part of the digital image with the classifier, wherein determining the digital image includes determining the object of the second class with a generative model depending on a label for the first class and/or depending on at least one pixel representing an object of the first class.

Abstract: A dual ion filter is arranged between upper and lower chambers of a substrate processing system. The dual ion filter includes upper and lower filters. The upper filter includes a first plurality of through holes configured to filter ions from a plasma in the upper chamber. The lower filter includes a second plurality of through holes configured to control plasma uniformity in the lower chamber. A diameter of the first plurality of through holes of the upper filter is less than a diameter of the second plurality of through holes of the lower filter. A number of the first plurality of through holes of the upper filter is greater than a number of the second plurality of through holes of the lower filter.

Abstract: Indicating repetitions at a UE in an NTN includes decoding a communication indicating a timing relationship value associated with a distance between a serving satellite and a farthest UE in the NTN. A PRACH communication is encoded for transmission. The PRACH communication includes an indication of a number of PRACH repetitions determined based on the timing relationship value. A RAR including an uplink (UL) grant corresponding to the UE and an indication of a number of RAR repetitions is decoded. The number of RAR repetitions is determined based on the timing relationship value. A PUSCH communication including an indication of a number of PUSCH repetitions is encoded. The number of PUSCH repetitions is determined based on the timing relationship value. A content resolution communication including an indication of a number of content resolution repetitions is decoded. The number of content resolution repetitions is determined based on the timing relationship value.

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: 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: 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: A computer-implemented method for training an augmented discriminator and a generator. The method includes: providing a training set comprising real training samples and artificial training samples for training of the augmented discriminator, wherein the artificial training samples are generated by the generator; assigning a data sequence to at least one data sample of the training set; wherein each pair of data sample and assigned data sequence is assigned to one of a plurality of classes such that, given the assigned one class and the assigned data sequence characterize whether the data sample is a real training sample or an artificial training sample; training the augmented discriminator to compute from pairs of data sample and assigned data sequence the respective class to which the corresponding pair is assigned; training the generator to generate artificial training samples such that the augmented discriminator is not able to correctly compute the aforementioned one class.

Abstract: Various aspects of the present disclosure generally relate to wireless communication and radar detection. In some aspects, a radar device may perform, at an initial listen before talk (LBT) frame boundary associated with an initial LBT frame of a plurality of LBT frames, an initial LBT procedure, wherein the initial LBT frame has a frame length that is larger than a propagation delay associated with a maximum detectable range associated with the radar device; and transmit a radar signal based at least in part on a successful result of the initial LBT procedure or an additional LBT procedure. Numerous other aspects are provided.

Abstract: Embodiments of the present disclosure provide enhanced system and methods for implementing generative converting 3D face landmarks. An enhanced disclosed system and non-limiting method effectively renders a third 3D face model of a first user that enables a second user to easily recognize the first user, where the second user is only familiar with a first face model that is significantly changed in a second face model of the first user in a current interaction of the first user and second user. This method effectively renders the third 3D face model of the first user that can gradually change from the first face model to the second face model, and can be easily recognized by the second user.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE), such as a vehicle UE may determine, based on one or more communication parameters of the UE, a radar field of view (FOV) for radar communications at the UE relative to a fixed frame of reference for the wireless communications system. The UE may determine a set of radar transmission parameters based on the radar FOV, where each radar transmission parameter of the set of radar transmission parameters is a function of the radar FOV. The UE may transmit a radar message using the set of radar transmission parameters according to the radar FOV relative to the fixed frame of reference.

Abstract: Certain aspects of the present disclosure provide techniques for wireless communication. A method that may be performed by a base station (BS), the method including determining a plurality of root sets, wherein each root set of the plurality of root sets comprise at least a first root and a second root. In some examples, the method includes transmitting signaling that indicates the plurality of root sets.

Abstract: A computer-implemented method for classifying whether an input signal, which comprises image and/or audio data, is anomalous or not with respect to a second data distribution using an anomaly classifier. The method includes: providing the input signal to the anomaly classifier; in the anomaly classifier, providing the input signal to a reference detector and a second detector; obtaining a reference value from the reference detector based on the input signal, the reference value characterizing the likelihood of the input signal to belong to a reference data distribution; obtaining a second value from the second detector based on the input signal, the second value characterizing the likelihood of the input signal to belong to the second data distribution; and providing an output signal, which characterizes a classification of the input signal as anomalous or not based on a comparison of the reference value and the second value.