Abstract: Provided are a data processing method and device, and a storage medium. The method includes: receiving configuration information of a blockchain from a second network element; and putting collected on-chaining information on the blockchain according to the configuration information of the blockchain.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for efficiently, quickly, and flexibly generating and providing pixel-wise classification predictions utilizing early exit heads of a multi-exit pixel-level prediction neural network. For example, the disclosed systems utilize a multi-exit pixel-level prediction neural network to generate classification predictions for a digital image on the pixel level. The multi-exit pixel-level prediction neural network includes a specialized architecture with early exit heads having unique encoder-decoder architectures for generating pixel-wise classification predictions at different early exit stages. In some embodiments, the disclosed systems implement a spatial confidence-adaptive scheme to mask certain predicted pixels to prevent further processing of the masked pixels and thereby reduce computation.

Abstract: Provided are a congestion control method and device, and a base station. The congestion control method includes: determining whether a traffic data flow transmitted by a base station is congested; setting an Internet protocol (IP) data packet in the traffic data flow when the traffic data flow transmitted by the base station is congested, where the set IP data packet is used for indicating that the traffic data flow transmitted by the base station is congested. The present disclosure solves the problem in the existing art that user throughput is affected because a base station only determines whether the base station is congested.

Abstract: Provided are a method and a device for load information interaction, a processor and a storage medium. The method includes: sending, by a first network node, a load request message to a second network node, where the load request message is used for indicating configuration information used by the second network node in reporting load information to the first network node; and receiving, by the first network node, the load information reported by the second network node according to the configuration information. The second network node and the first network node belong to different logical nodes in a network. The technical problem that load management cannot be performed when the second network node and the first network node belong to different logical nodes in related technology is solved, and the maximum performance of the network is fully exhibited.

Abstract: An intelligent smog-penetrating optical imaging detection device and a method of thereof, and belongs to the technical field of photoelectric imaging. The intensity information, the spectrum information, and the polarization information of light are organically combined, the three functions of intensity imaging, spectrum imaging and polarization imaging can be achieved, traditional imaging detection is beneficially supplemented, smog can be penetrated, the image contrast of imaging is improved, and therefore the working distance is increased. The intensity information reflects the detection distance, the target shape, the target size and the like; the spectrum information reflects material components, surface morphology and the like of a space target; the polarization information reflects the material and roughness of the target and the contrast with the background; and the intensity, spectrum and polarization three-dimensional information is jointly applied, the image contrast can be increased by 2-3 times.

Abstract: Provided are a data transmission method and apparatus, a data sending method and apparatus, and a data transmission system. The data transmission method includes: receiving, by a second network node, data which carries a protocol data unit (PDU) and is sent by a first network node, where the PDU at least includes quality of service (QOS) information bearing the data, and the QOS information includes at least one of: a QOS flow identifier (QFI) indication of the data, or a fifth-generation QOS identifier (5QI) corresponding to the data.

Abstract: The present application provides a network optimization method, including: sending a session setup request message to a client device to request the client device to perform measurement configuration on a designated network side device and perform measurement configuration on a terminal device connected to the designated network side device; receiving a measurement report message of the designated network side device and a measurement report message of the terminal device; determining, according to pre-acquired machine learning description information, whether to perform collaborative training with the client device; and performing designated model training processing for network optimization based on whether to perform collaborative training with the client device and measurement data in the received measurement report messages, and sending a model training processing result to the client device to instruct the client device to obtain a network optimization action according to the model training processing r

Abstract: Provided are a data transmission method and apparatus and a computer storage medium. The method may include: a source Distributed Unit (DU) reports a packet data convergence protocol (PDCP) transmission state report to a source Centralized Unit (CU), where the PDCP transmission state report enables the CU to determine which PDCP protocol data unit (PDU) data is not successfully received by a UE; and the PDCP PDU data which is not successfully received by the UE are retransmitted to the UE via a target DU.

Abstract: Methods, systems, and devices for configuring quality-of-experience (QoE) measurements in mobile cellular networks are described. An example method for wireless communication includes generating, by a network node based on a first QoE measurement configuration, a second QoE measurement configuration, and transmitting, to a wireless device, a first radio resource control message comprising the second QoE measurement configuration and an activation configuration, wherein the first QoE measurement configuration configures the wireless device to perform QoE measurements that are not visible to the network node and the second QoE measurement configuration configures the wireless device to perform QoE measurement that are visible to the network node.

Abstract: Provided are a non-public network measurement method and apparatus, a device, and a storage medium. The method includes: sending, through an air interface, a radio resource control (RRC) message including a non-public network (NPN) measurement configuration to at least one selected user equipment (UE), to instruct the UE to perform corresponding NPN measurement; and receiving a measurement report of the NPN measurement from the UE through an air interface. The measurement report includes an NPN measurement result of a corresponding UE. In the embodiment of the present disclosure, the NPN measurement configuration is sent through the RRC message, and thus NPN network information is detected, thereby facilitating NPN network capacity expansion and NPN network optimization.

Abstract: Techniques are described to indicate traffic awareness information by a network device. An example wireless communication method includes communicating, by a first network function of a network node, traffic awareness information to a second network function of the network node, wherein the traffic awareness information includes traffic characteristics of one or more quality of service (QoS) flows between the network node and a communication node.

Abstract: A network optimization method includes determining network side measurement control information according to pre-acquired policy information to be satisfied by a network; sending a session setup request to a designated network side device to request the designated network side device to perform, according to the network side measurement control information, measurement configuration on the designated network side device and measurement configuration on a user equipment (UE) connected to the designated network side device; receiving a measurement report of the designated network side device and a measurement report of the UE; and performing, based on measurement data in received measurement reports and the policy information, machine learning for network optimization to obtain a network optimization operation instruction, where the network optimization operation instruction is used for indicating the designated network side device and the UE to perform the network optimization according to the network optimiza

Abstract: Provided are a location prediction method and apparatus, a node and a storage medium. The method includes: a server obtaining a measurement report message sent by a base station, where the measurement report message includes historical location measurement information reported by at least one UE and/or historical location measurement information of the at least one UE measured by the base station; and the server determining prediction location information of the at least one UE at a first time point or in a first time period according to the measurement report message, and sending notification information to the base station according to the prediction location information. By introducing measurement information in multiple dimensions, the accuracy of predicting the location of UE can be effectively improved.

Abstract: The end-to-end experience of a wireless customer depends on at least data throughput, data loss, and latency, as well as other characteristics. The user’s quality of experience (QoE) can be determined based on applications and measurements taken at the application layer of the user’s user equipment (UE) and information at the session level at the UE initiated and configured by an operator at the start of the session. The QoE is an application layer measurement configured by the operator and reported inside the application layer. When a UE is performing an inter-system handover, the QoE measurement configuration of the current session cannot be transferred from the source network to the target network.

Abstract: The coastal ecosystem carbon pool estimation method of the invention belongs to the field of environmental assessment, and includes the following steps: (a) determining the spatial boundary of the coastal ecosystem; (b) determining the dominant plant classification area of the coastal ecosystem; (c) calculating the carbon source of the freshwater plant dominant area; (d) size setting of carbon source sampling point in coastal ecosystem; (e) sampling method of carbon source sampling point in coastal ecosystem; (f) carbon source estimation method in coastal ecosystem.

Abstract: Embodiments of this application provide a dual Wi-Fi connection method and an electronic device. While exchanging data with a first access point, a first electronic device in the embodiments of this application may quickly establish a Wi-Fi connection with a second access point based on an association relationship between the first access point and the second access point, and after establishing the Wi-Fi connection with the second access point, exchange data with the first access point and the second access point simultaneously, to effectively shorten a duration taken for accessing the second access point, improve the throughput of the first electronic device and the stability of data transmission, and further improve the user experience.

Abstract: Presented are a systems, methods, apparatuses, or a computer-readable media for uplink packet duplication transmission. A host radio access network (RAN) node hosting a packet data convergence protocol (PDCP) entity may determine a location of a primary radio link control (RLC) entity. The host RAN node may transmit, to an assisting RAN node, the location of the primary RLC entity.

Abstract: Disclosed are a location prediction method and apparatus, a network element, a base station and a non-transitory computer-readable storage medium. The position prediction method may include: receiving, by a location service network element, a Minimization of Drive Tests (MDT) measurement information message sent by a base station, wherein the location service network element is a separate network element or a network element inside the base station, and the MDT measurement information message carries history location measurement information of at least one user equipment (UE); determining, by the location service network element, predicted location information of the at least one UE for a first time point or a first time period according to the history location measurement information of the at least one UE; and sending, by the location service network element, the predicted location information to the base station.

Abstract: The present disclosure discloses a method for the magnetism stabilizing treatment of a permanent magnet material. The method can include the following steps: providing a permanent magnet material having a positive temperature coefficient of coercivity; magnetizing the permanent magnet material at a temperature T3 with a range of ?200 degree centigrades to 200 degree centigrades; and performing a magnetism stabilizing treatment towards the permanent magnet material with temperature decreased in a range of the temperature T3 to a temperature T4, or at the temperature T3.

Abstract: A mechanism is described for facilitating slimming of neural networks in machine learning environments. A method of embodiments, as described herein, includes learning a first neural network associated with machine learning processes to be performed by a processor of a computing device, where learning includes analyzing a plurality of channels associated with one or more layers of the first neural network. The method may further include computing a plurality of scaling factors to be associated with the plurality of channels such that each channel is assigned a scaling factor, wherein each scaling factor to indicate relevance of a corresponding channel within the first neural network. The method may further include pruning the first neural network into a second neural network by removing one or more channels of the plurality of channels having low relevance as indicated by one or more scaling factors of the plurality of scaling factors assigned to the one or more channels.