Abstract: This application relates to the field of wireless communications technologies, and discloses an encoding method and apparatus, to improve accuracy of reliability calculation and ordering for polarized channels. The method includes: obtaining a first sequence used to encode K to-be-encoded bits, where the first sequence includes sequence numbers of N polarized channels, the first sequence is same as a second sequence or a subset of the second sequence, the second sequence comprises sequence numbers of Nmax polarized channels, and the second sequence is the sequence shown in Sequence Q11 or Table Q11, K is a positive integer, N is a positive integer power of 2, n is equal to or greater than 5, K?N, Nmax=1024; selecting sequence numbers of K polarized channels from the first sequence; and performing polar code encoding on K the to-be-encoded bits based on the selected sequence numbers of the K polarized channels.

Abstract: A data processing method for a data processing system having a first communications node and a second communications node where the first communications node corresponds to a first blockchain node and the second communications node corresponds to a second blockchain node that maintains a same block chain as the first blockchain node, the method including obtaining, by the first communications node, to-be-verified data when a terminal camps on a target cell, where the to-be-verified data is obtained based on camping information of the terminal, and the target cell is a cell within signal coverage of the first communications node sending, by the first communications node, the to-be-verified data to the second communications node, so that the second communications node verifies the to-be-verified data based on the second blockchain node, and obtaining, by the first communications node, a target block if the verification succeeds.

Abstract: Improved lossless entropy coding techniques for coding of image data include selecting a context for entropy coding based on an ordered scan path of possible context locations. A symbol for a current location within a source image may be entropy coded based on a context of prior encoded symbols of other locations within source images, where the context is selected based on an ordered scan path enumerating a series of potential context locations within one or more source images. To select a context, a predetermined number of prior symbols may be selected by qualifying or disqualifying locations in the scan path, and then the current symbol may be encoded with a context based on prior symbols corresponding to the first qualifying context locations in the order of the scan path.

Abstract: The present disclosure relates to artificial intelligence (AI) operation processing methods apparatuses. One example method includes obtaining a first group identifier, obtaining a trigger message sent by a network device, where the trigger message includes first control information, the first control information indicates a first time-frequency resource, the first time-frequency resource carries N pieces of first scheduling information, each of the N pieces of first scheduling information includes a respective second group identifier and respective AI operation information and indicates a terminal device in a user group indicated by the respective second group identifier to perform an AI operation corresponding to the respective AI operation information, determining target AI operation information when the first group identifier matches a target group identifier, and starting a target AI operation based on the target AI operation information.

Abstract: This application provides an example communication method. The example method includes a terminal device obtains a first message, where the first message includes target adjustment information. The terminal device obtains a second message, where the second message includes a timing advance (TA). The terminal device adjusts an uplink sending time based on the target adjustment information and the TA.

Abstract: This application provides a data transmission method. The method includes: receiving a first PDCCH, where the first PDCCH includes first DCI, the first DCI indicates a first resource, and the first resource is used to carry first uplink data; determining a first time period or a second time period, where the first time period includes a time period for monitoring a second PDCCH, and the second time period does not include the second PDCCH; and monitoring the second PDCCH based on the first time period or the second time period.

Abstract: Techniques are disclosed for improved video coding with virtual reference frames. A motion vector for prediction of a pixel block from a reference may be constrained based on the reference. In as aspect, if the reference is a temporally interpolated virtual reference frame with corresponding time close to the time of the current pixel block, the motion vector for prediction may be constrained magnitude and/or precision. In another aspect, a bitstream syntax for encoding the constrained motion vector may also be constrained. In this manner, the techniques proposed herein contribute to improved coding efficiencies.

Abstract: A small-file storage optimization system based on a virtual file system in a KUBERNETES user-mode application which is applied to a target file system includes a network file system including a network file system server and a network file system client, a user-mode application mounted on a shared directory exposed by the network file system server through the network file system client, and a virtual file system including a virtual file system client and a virtual file system server. A file block creating and formatting module in the virtual file system server creates a virtual file block for storing small files on one or more object storage target devices of the target file system, and the virtual file block is mounted on the shared directory exposed by the network file system server.

Abstract: A small-file storage optimization system based on a virtual file system in a KUBERNETES user-mode application which is applied to a target file system includes a network file system including a network file system server and a network file system client, a user-mode application mounted on a shared directory exposed by the network file system server through the network file system client, and a virtual file system including a virtual file system client and a virtual file system server.

Abstract: The present invention relates to fields of clinical application of nerve defect repair and the medical three-dimensional (3D) printing technology, and provides an integrated visualization method for three-dimensional (3D) reconstruction of internal structure of human peripheral nerves. The method comprises the following steps: obtaining human peripheral nerves, preparing nerve specimens ex vivo by staining with an iodine preparation in combination with a freeze-drying method; scanning the pretreated peripheral nerves using Micro CT to acquire lossless two-dimensional images, and performing binarization processing to the two-dimensional images, then conducting image segmentation based on textural features to acquire images of nerve fascicles; finally, reconstructing the segmented images into a visualization model by using a supercomputer.

Abstract: The present invention relates to fields of clinical application of nerve defect repair and the medical three-dimensional (3D) printing technology, and provides an integrated visualization method for three-dimensional (3D) reconstruction of internal structure of human peripheral nerves. The method comprises the following steps: obtaining human peripheral nerves, preparing nerve specimens ex vivo by staining with an iodine preparation in combination with a freeze-drying method; scanning the pretreated peripheral nerves using Micro CT to acquire lossless two-dimensional images, and performing binarization processing to the two-dimensional images, then conducting image segmentation based on textural features to acquire images of nerve fascicles; finally, reconstructing the segmented images into a visualization model by using a supercomputer.