Abstract: The present invention provides a microchannel heat sink with plural microchannels, each having a respective inlet and outlet to permit flow, in particular two-phase flow, of a working fluid. The plural microchannels are arranged such that adjacent microchannels accommodate flow of working fluid in opposite directions and are thermally coupled to each other to enable heat exchange between the corresponding adjacent microchannels. In one aspect, a microchannel inlet is positioned at an angle (e.g., 90 degrees) with respect to its outlet. The plural microchannels define parallel longitudinal axes that are optionally arranged on the same plane and/or side-by-side in a single layer. Further, in one aspect, each microchannel cross-sectional area increases as the channel length progresses from an upstream end (e.g., adjacent to the inlet) to a downstream end (e.g., adjacent to the outlet) of the corresponding microchannel.

Abstract: Computing system enhancements make container instantiation faster, reduce layer content storage demands, and make more container image formats available. A container instantiation location sends a container image pull request to a container registry, receives an image manifest, sends a layer mount request to the registry instead of a layer content download request, receives a layer mount, optionally repeats for additional layers, creates a union file system spanning the layers, and launches a container process based on the union file system without first downloading all the layer content.

Abstract: Systems and methods for linking Physical Downlink Control Channel (PDCCH) candidates are provided herein. In some embodiments, a method includes: receiving a configuration of a first and second Control Resource Set (CORESET) associated with a first and second Search Space (SS) set; determining that the first and second SS set are configured with a common set of parameters; activating the first and second CORESET with a first and second TCI state; linking a first PDCCH candidate in a first PDCCH monitoring occasion to a second PDCCH candidate in a second PDCCH monitoring occasion; receiving a PDCCH in the first PDCCH candidate and the PDCCH in the second PDCCH candidate; and detecting the PDCCH in the first and the second PDCCH candidates. Some embodiments might provide a simple way for linking PDCCH candidates in two SS sets to support both intra-slot and inter-slot PDCCH repetition in either TDM or FDM manner.

Abstract: In one embodiment, a method performed by a wireless device comprises receiving Downlink Control Information (DCI) that schedules Physical Uplink Shared Channel (PUSCH) repetitions to Transmission/Reception Points (TRPs) where the PUSCH is configured with a maximum rank larger than 2. The DCI comprises an antenna ports field that indicates two or more Demodulation Reference Signal (DMRS) ports and either: a single PTRS-DMRS association field or two PTRS-DMRS association fields. The method further comprises determining a DMRS port associated with a Phase Tracking Reference Signal (PTRS) port for PUSCH transmissions to a first TRP based on either a most significant bit (MSB) of the single PTRS-DMRS association field or the first PTRS-DMRS association field and determining a DMRS port associated with a PTRS port for PUSCH transmissions to a second TRP based on either a least significant bit (LSB) of the single PTRS-DMRS association field or the second PTRS-DMRS association field.

Abstract: The present disclosure provides a magnetic component and a power module, relating to the technical field of power electronics; the magnetic component provided by the present disclosure includes: a first heat sink, a magnetic core extending in a transverse direction and a winding structure wound on the magnetic core, the winding structure includes at least a first coil and a second coil arranged adjacently along the transverse direction, a gap is provided between the first coil and the second coil, at least part of the first heat sink is arranged in the gap, the first heat sink is in thermal contact with the first coil, the second coil and the magnetic core.

Abstract: Provided in embodiments of the disclosure are a method and apparatus for video processing, an electronic device, and a computer storage medium. In one embodiment, a method for video processing includes: identifying, by a processor, video segments from a video, each video segment associated with a shot of the video; computing, by the processor, degrees of similarity among the video segments, the degrees of similarity associated with corresponding segmentation levels; and segmenting, by the processor, the video segments based on the degrees of similarity and the segmentation levels to generate sets of scene-based video segments, each set of scene-based video segment associated with a corresponding segmentation level.

Abstract: Embodiments of the disclosure provides methods and apparatuses for data processing and video cover generation. The method for video cover generation comprises: receiving a video for processing, a processing request for the video, and a video cover generation condition; segmenting the video based on the processing request to obtain a sequence of target clips; scoring target clips in the sequence of target clips based on a pre-configured algorithm to obtain scores for the target clips; after weighting the scores of target clips satisfying the video cover generation condition, weighting the scores of target clips associated with a video category of the video; and generating, based on a weighting process result, a personalized video cover attracting more user attention.

Abstract: Embodiments of the disclosure provides methods and apparatuses for video processing. In one embodiment, the video processing method comprises: obtaining at least one video from a video repository as a video to be processed; performing semantic recognition on the video in one or more semantic recognition dimensions to obtain one or more video label data items corresponding to the video in the one or more semantic recognition dimensions; generating at least one candidate label combination based on at least one of the one or more video label data items; determining, based on a target label combination selected by a user from the at least one candidate label combination, one or more video clips in the video corresponding to at least one video label in the target label combination; and generating at least one target video clip corresponding to the target label combination based on at least one of the one or more video clips.

Abstract: Computing system enhancements make container instantiation faster, reduce layer content storage demands, and make more container image formats available. A container instantiation location sends a container image pull request to a container registry, receives an image manifest, sends a layer mount request to the registry instead of a layer content download request, receives a layer mount, optionally repeats for additional layers, creates a union file system spanning the layers, and launches a container process based on the union file system without first downloading all the layer content.

Abstract: The present invention provides a microchannel heat sink with plural microchannels, each having a respective inlet and outlet to permit flow, in particular two-phase flow, of a working fluid. The plural microchannels are arranged such that adjacent microchannels accommodate flow of working fluid in opposite directions and are thermally coupled to each other to enable heat exchange between the corresponding adjacent microchannels. In one aspect, a microchannel inlet is positioned at an angle (e.g., 90 degrees) with respect to its outlet. The plural microchannels define parallel longitudinal axes that are optionally arranged on the same plane and/or side-by-side in a single layer. Further, in one aspect, each microchannel cross-sectional area increases as the channel length progresses from an upstream end (e.g., adjacent to the inlet) to a downstream end (e.g., adjacent to the outlet) of the corresponding microchannel.

Abstract: Provided in embodiments of the disclosure are a method and apparatus for video processing, an electronic device, and a computer storage medium. In one embodiment, a method for video processing includes: identifying, by a processor, video segments from a video, each video segment associated with a shot of the video; computing, by the processor, degrees of similarity among the video segments, the degrees of similarity associated with corresponding segmentation levels; and segmenting, by the processor, the video segments based on the degrees of similarity and the segmentation levels to generate sets of scene-based video segments, each set of scene-based video segment associated with a corresponding segmentation level.

Abstract: A spatiotemporal action detection method includes performing object detection on all frames of a sample video to obtain a candidate object set; calculating all interframe optical flow information on the sample video to obtain a motion set; constructing a spatiotemporal convolution-deconvolution network of an attention mechanism and a motion attention mechanism of an additional object; adding both a corresponding sparse variable and a sparse constraint to obtain a network structure S after performing spatiotemporal convolution processing on each time segment of the sample video; training the network structure S with an objective function based on classification loss and loss of the sparse constraint of cross entropy; and calculating an action category and a sparse coefficient corresponding to each time segment of a test sampled video to obtain an object action spatiotemporal location.

Abstract: The present invention discloses a method and system for selecting an image region that facilitates blur kernel estimation, in which the method includes: calculating a relative total variation value of each pixel in a blurred image to obtain a relative total variation mapping image; setting a threshold value to determine whether respective pixel in the image is a boundary pixel or not; then sampling the blurred image and its relative total variation mapping image to obtain a series of image patches; and finally counting the number of boundary pixels in each mapping image patch and selecting out an image region that facilitates blur kernel estimation. According to the method and the system, the problems of excessive dependency on operator experience, low efficiency and the like in the existing region selection methods are effectively solved. The image region that facilitates blur kernel estimation is automatically selected out.

Abstract: A spatiotemporal action detection method includes performing object detection on all frames of a sample video to obtain a candidate object set; calculating all interframe optical flow information on the sample video to obtain a motion set; constructing a spatiotemporal convolution-deconvolution network of an attention mechanism and a motion attention mechanism of an additional object; adding both a corresponding sparse variable and a sparse constraint to obtain a network structure S after performing spatiotemporal convolution processing on each time segment of the sample video; training the network structure S with an objective function based on classification loss and loss of the sparse constraint of cross entropy; and calculating an action category and a sparse coefficient corresponding to each time segment of a test sampled video to obtain an object action spatiotemporal location.

Abstract: Embodiments of the disclosure provides methods and apparatuses for data processing and video cover generation. The method for video cover generation comprises: receiving a video for processing, a processing request for the video, and a video cover generation condition; segmenting the video based on the processing request to obtain a sequence of target clips; scoring target clips in the sequence of target clips based on a pre-configured algorithm to obtain scores for the target clips; after weighting the scores of target clips satisfying the video cover generation condition, weighting the scores of target clips associated with a video category of the video; and generating, based on a weighting process result, a personalized video cover attracting more user attention.

Abstract: Embodiments of the disclosure provides methods and apparatuses for video processing. In one embodiment, the video processing method comprises: obtaining at least one video from a video repository as a video to be processed; performing semantic recognition on the video in one or more semantic recognition dimensions to obtain one or more video label data items corresponding to the video in the one or more semantic recognition dimensions; generating at least one candidate label combination based on at least one of the one or more video label data items; determining, based on a target label combination selected by a user from the at least one candidate label combination, one or more video clips in the video corresponding to at least one video label in the target label combination; and generating at least one target video clip corresponding to the target label combination based on at least one of the one or more video clips.

Abstract: The present invention discloses a method and system for selecting an image region that facilitates blur kernel estimation, in which the method includes: calculating a relative total variation value of each pixel in a blurred image to obtain a relative total variation mapping image; setting a threshold value to determine whether respective pixel in the image is a boundary pixel or not; then sampling the blurred image and its relative total variation mapping image to obtain a series of image patches; and finally counting the number of boundary pixels in each mapping image patch and selecting out an image region that facilitates blur kernel estimation. According to the method and the system, the problems of excessive dependency on operator experience, low efficiency and the like in the existing region selection methods are effectively solved. The image region that facilitates blur kernel estimation is automatically selected out.

Abstract: A method for estimating a blur kernel size, the method including: (1) pre-processing a blurred image, to obtain an image, so that a size of the image satisfies an image input size of a multi-class convolutional neural network (CNN); (2) inputting the image into a multi-class CNN with completed training, to obtain a blur-kernel-size probability distribution vector; and (3) comparing each element in the blur-kernel-size probability distribution vector, so that an estimated blur kernel size of the blurred image is the blur kernel size corresponding to a largest element. The invention also provides a system for estimating a blur kernel size. The system includes an image pre-processing module, a training-set synthesizing module, a multi-class CNN module, and a blur kernel size estimation module.

Abstract: A method for repairing a dynamic link library (DLL) file includes: reading an import section in an executable file; determining, according to DLL file information recorded in the import section and a pre-established correspondence between a DLL file and a save path, that a DLL file is lost; and notifying, when an instruction for running the executable file is received, that the DLL file is lost, and calling an installation package of the DLL file to repair the DLL file. The apparatus includes: a reading module, a determining module and a repairing module.

Abstract: A method for estimating a blur kernel size, the method including: (1) pre-processing a blurred image, to obtain an image, so that a size of the image satisfies an image input size of a multi-class convolutional neural network (CNN); (2) inputting the image into a multi-class CNN with completed training, to obtain a blur-kernel-size probability distribution vector; and (3) comparing each element in the blur-kernel-size probability distribution vector, so that an estimated blur kernel size of the blurred image is the blur kernel size corresponding to a largest element. The invention also provides a system for estimating a blur kernel size. The system includes an image pre-processing module, a training-set synthesizing module, a multi-class CNN module, and a blur kernel size estimation module.