Abstract: This disclosure provides a data sending method and receiving method, and user equipment thereof, and relates to the field of communications technologies. The data receiving method applied to user equipment includes: determining whether a Medium Access Cntrol (MAC) Protocol Data Unit (PDU) received by the user equipment includes a reserved Logical Channel Identity (LCID) value; and when the MAC PDU includes a reserved LCID value, discarding a Service Data Unit (SDU) or sub-PDU corresponding to the reserved LCID value in the MAC PDU.

Abstract: Embodiments of this disclosure provide a serving node update method and a device. The method includes: sending a first message to a target node; receiving, from the target node, a second message used for responding to the first message; and sending a third message to a terminal device when the second message indicates that the target node rejects a multi-connectivity serving node update, where the third message is used to indicate the terminal device to perform a serving node update in a legacy serving node update manner.

Abstract: This application discloses a mode switching method, a terminal, and a network-side device. The method may be applied to a target network-side device, and includes: reserving a multicast air interface resource in a case that multicast quality of service QoS information is received from a multicast broadcast network function MB NF, where the multicast air interface resource is used for a terminal to receive multicast service data in a switched-to target mode, and the multicast QoS information corresponds to the multicast service data; and sending the multicast air interface resource to a source network-side device or the MB NF.

Abstract: Systems and methods for dynamically filtering choices include identifying, with an indecisiveness detector module, a state of a user, determining, with the indecisiveness detector module, whether the state of the user includes an indecisive behavior, identifying, with a choice identifier module, a state of an environment of the user, identifying, with the choice identifier module, a set of available choices from the state of the environment, receiving, with a processor, a set of past choices and a set of past user decisions relating to the set of past choices, and generating, with a decision making model, a predicted choice from the set of available choices based on the set of past choices and the set of past user decisions in response to determining that the state of the user includes an indecisive behavior.

Abstract: A computer-implemented method comprises receiving an input associated with the arrival of an entity, performing a classification on the input to determine a purpose of the arrival of the entity, and based on a determined classification of the purpose of the arrival of the entity, invoking an action.

Abstract: A computer-implemented method of learning sensory media association includes receiving a first type of nontext input and a second type of nontext input; encoding and decoding the first type of nontext input using a first autoencoder having a first convolutional neural network, and the second type of nontext input using a second autoencoder having a second convolutional neural network; bridging first autoencoder representations and second autoencoder representations by a deep neural network that learns mappings between the first autoencoder representations associated with a first modality and the second autoencoder representations associated with a second modality; and based on the encoding, decoding, and the bridging, generating a first type of nontext output and a second type of nontext output based on the first type of nontext input or the second type of nontext input in either the first modality or the second modality.

Abstract: A cell selection method, a cell selection control method and a related device are provided. The cell selection method includes: obtaining cell assistance information of an access network; and performing a cell selection based on the cell assistance information and slice assistance information. The slice assistance information is used to assist in performing the cell selection.

Abstract: Data retransmission method is disclosed. The method includes: obtaining a mapping relationship between GTP-U sequence numbers of N data packets sent by a source node and source PDCP sequence numbers assigned to the N data packets by the source node; and performing data retransmission based on the mapping relationship.

Abstract: Embodiments of this application provide a device interaction method and a core network device. The method includes: receiving, by a first core network device, identifier information of at least one UE sent by a first device, where the at least one UE includes at least one of the following: a UE that has established UE-to-network relay connection with a first UE and a UE that is to establish UE-to-network relay connection with the first UE; and interacting, by the first core network device based on identifier information of a second UE, with a second core network device, where the second UE is any one of the at least one UE; where the first core network device is a core network device serving the first UE, and the second core network device is a core network device serving the second UE.

Abstract: Embodiments of the present application provide a state indication method, a device, and a system. The method comprises: a relay core network device receives first state indication information sent by a first device, the first state indication information comprising at least one of first indication information and second indication information, the first indication information instructing a relay UE to perform UE-to-network relay communication, the second indication information instructing the relay UE to perform UE-to-network relay communication for an emergency service, and the first state indication information being used for determining not to initiate a NAS signaling connection release process of the relay UE.

Abstract: Embodiments of this disclosure provide a serving node update method and a device. The method includes: sending a first message to a target node; receiving, from the target node, a second message used for responding to the first message; and sending a third message to a terminal device when the second message indicates that the target node rejects a multi-connectivity serving node update, where the third message is used to indicate the terminal device to perform a serving node update in a legacy serving node update manner.

Abstract: A system and method for configuring a device includes using a machine learning model to generate a user behavior model based on user behavior data. The user behavior data may include time series data collected from user interactions with a first device, and the machine learning model may include a classification model configured to classify the user behavior data into the one or more classifications. A mapping may be created by training a machine learning model, using user behavior models from a plurality of users and device settings from the plurality of users, to identify one or more relationships between device settings and classifications of the user behavior data. The system and method configures one or more settings of a second device based on the user behavior model and the mapping.

Abstract: A transmission mode conversion indication method includes: sending a first message to a core network or sending a second message to a terminal device, so as to indicate that a transmission mode conversion is required, where the first message carries first user information and first multicast group information.

Abstract: Provided are a random access method, a terminal device and a network device. The random access method includes transmitting a two-step random access request message to a network device. A data part is carried in the two-step random access request message, and the data part is acquired through performing layer-two processing in accordance with layer-two configuration information.

Abstract: The embodiments of the disclosure provide a bandwidth switching method and a user equipment. The method includes: when a BWP switching command is received while successfully receiving the random access completion message of the non-contention-based random access process, determine the non-contention-based random access process has been completed successfully in accordance with random access completion message, and determine not to perform the BWP switching process, or perform the BWP switching process in accordance with the random access completion message and the BWP switching command.

Abstract: A computer-implemented method includes receiving first inputs associated with a first modality and second inputs associated with a second modality; processing the received first and second inputs with convolutional neural networks (CNN), wherein a set of first weights are used to handle the first inputs and a second set of weights are used to handle the second inputs; determining a loss for each of the first and the second inputs based on a loss function that applies the first set of weights, the second set of weights, and a presence of a co-occurrence; generating a shared feature space as an output of the CNNs, wherein a distance between cells associated with the first inputs and the second inputs in the shared feature space is determined based on the loss associated with each of the first inputs and the second inputs; and based on the shared feature space, providing an output.

Abstract: A method includes fitting a ML trained model to data features, the fitting generates complete data feature-set outputs that are associated with a first set of accuracy values, iteratively fitting, after an iterative removal of each data feature from the data feature-set, the ML trained model to subsets of the plurality of data features to determine respective reduced feature-set outputs, each subset lacks a different data feature of the plurality of data features, determining one or more of the reduced feature-set outputs as corresponding to a second set of accuracy values, designating the iteratively removed data features as accuracy-modifying data features, generating a first linear model, generating a second linear model based on one of the accuracy-modifying data features having a weight that is highest relative to respective different weights of the remaining ones of the accuracy-modifying data features, and identifying the second linear model as a generative model.

Abstract: The embodiments of the present disclosure provide a method for supporting quality of service of time-sensitive communication and a communication device. The method includes: obtaining first information, where the first information includes at least one of the following: transfer configuration information of a time-sensitive data stream, or bridge capability information; and performing a first operation according to the first information.

Abstract: A method implemented by a processor of a device, the method including determining one or more user values, determining a prompt requiring a decision, and receiving a user selection to one or more choice options related to the one or more user values and pertaining to the prompt requiring a decision. The method further includes comparing the user selection to a risk-neutral utility function and assessing a risk of a potential decision based on the comparison.

Abstract: Electronic devices and methods for displaying information on electronic displays of electronic devices based on learned user behavior are disclosed. In one embodiment, an electronic device includes an electronic display, a processor, and a non-transitory computer-readable medium storing instructions that, when executed by the processor, causes the processor to cause for display on the electronic display a selected representation of information among a plurality of representations based at least in part on learned behavior of a user.