Abstract: A method, an apparatus, a device, and a storage medium for interaction are provided. In the method, an input control is presented in a first user interface. A pattern received via the input control is presented in a first user interface, the pattern includes one or more lines. A first image is obtained based on the pattern, the first image visually at least partially matches with the pattern. The first image is presented. In response to a predetermined condition being satisfied, at least a portion of a second image captured in real time is presented together with at least a portion of the first image.

Abstract: Provided are a communication method and device and a storage medium. A communication method applied to a first communication node includes: receiving a network optimization operation instruction, and sending a performance feedback request message to a second communication node; receiving performance feedback measurement information corresponding to the performance feedback request message and sent by the second communication node; and determining an optimization operation for a target model according to the performance feedback measurement information.

Abstract: A method, network device and storage medium for DC in cellular wireless communication systems are disclosed. A master node (MN) may provide predicted User Equipment (UE) trajectory and other predicted MN or Secondary Node (SN) information inferred from one or more AI/ML models to the SN for the SN to effectuate addition, selection, configuration, modification, change, and/or removal of resources, primary cells, secondary cells, cell groups, and the like to optimize DC. Likewise, the SN may provide predicted UE trajectory and other predicted information of itself and other target SNs inferred from one or more AI/ML models to the MN to effectuate changes and optimization in DC configuration and selection of target SN and target cells therein. Various mechanisms based on expanding existing MN-SN messaging framework or new MN-SN messaging framework are disclosed in order to effectuate the transfer of the AI predictions for DC optimization.

Abstract: The present disclosure describes methods, system, and devices for determining a target cell identifier (ID) for calculating a message authentication code for integrity (MAC-I). One method includes determining, by a user equipment (UE), a target cell ID for calculating an authentication code corresponding to a cell by: receiving, by the UE, system information broadcasted from a network node; determining, by the UE, a network type of the cell based on the system information; and determining, by the UE, the target cell ID based on the network type and the system information. Another method includes determining, by a network node, a target cell ID for calculating an authentication code corresponding to a cell by: broadcasting, by the network node, system information to a UE; and determining, by the network node, the target cell ID based on a network type of the cell.

Abstract: There is provided a method for multipath transmission in wireless networks, which includes receiving an input packet at a source node, encoding the input packet into multiple coded sub-packets by applying codes for multipath transmission, and transmitting the multiple coded sub-packets to a receiving end via multiple paths, wherein each path i?{1, . . . , N}.

Abstract: A wireless communication method includes: receiving, during handover, a target quality of experience (QoE) information and a quality of experience (QoE) assistance information; generating a predicted QoE information based on the QoE assistance information; and determining whether a target QoE can be satisfied after the handover based on the predicted QoE information with the target QoE information.

Abstract: Provided are a twist-bend nematic (NTB) LC dimer-based material and use thereof, and an LC-based cholesteric heliconical (CH) material and use thereof. The NTB LC dimer-based material is at least one selected from the group consisting of CBnCB, CBnOCB, and CBOnOCB, with n being a positive integer of 3 to 15. Based on ultra-stable properties of the material, the disclosure further provides the LC-based CH material, which uses the LC dimer-based material as a key raw material and integrates a conventional nematic LC monomer material and a chiral molecule.

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: This disclosure generally relates to wireless communication networks and is particularly directed to cell coverage and capacity optimization (CCO) in a radio access network in the context of Self-Optimization Network (SON) based on artificial intelligence predictions. For example, radio access network nodes may be configured to assist one another in performing predictive cell CCO for a future time. For cell coverage optimization, such predictive cell optimization may be performed at one radio access network node based on predicted coverage modification information items provided by another radio access network node. The predicted coverage modification information items may be obtain based on network coverage prediction based on artificial intelligence using current and historical network condition, status, and measurement data of current and neighboring cells. As an example, such cell coverage modification may include predictive beam reconfigurations.

Abstract: A wireless communication method includes obtaining input information, including at least one of: slice measurement result information, one or more first pieces of information, one or more second pieces of information, or inference feedback information and using the input information to perform at least one of model training of a slice radio resource management model or generating an inference output with the slice radio resource management model.

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: An LDMOS transistor can include: an intrinsic region and a termination region distributed along, where the intrinsic region includes a semiconductor region of a first doped type, a body region of a second doped type extending from the upper surface of the semiconductor region into the interior of the semiconductor region, a drift region located in the semiconductor region, the drift region including at least one first implant region of the first doped type and at least one second implant region of the second doped type, where the at least one second implant region is separated from the body region, a source region of the first doped type located in the body region, and a drain region of the first doped type located in the semiconductor region, where the termination region includes a third implant region of the second doped type being in contact with the second implant region.

Abstract: A hardware encryption module, a chip and an encryption method. The hardware encryption module comprising a control unit and a storage unit; the control unit is connected to the storage unit, receives external instructions, determines an encryption status based on an encryption indicator in an encryption bit address of the storage unit, generates a first control timing sequence for controlling erase of the storage unit based on an external erase instruction, and generates a second control timing sequence for controlling reading/writing of the storage unit based on the encryption status and an external read/write instruction; when in an encrypted mode, only the program area is encrypted against reading, and writing operations to the encryption bit address are prohibited. All encryption behaviors of the present disclosure are effective only for the program area and are not effective for the data area.

Abstract: This disclosure is generally directed to wireless communication systems and methods and relates particularly to a mechanism for implementing an artificial intelligence framework for adaptively configure the over-the-air communication interfaces of the wireless communication systems. AI network configuration functions may be provided as services for AI-assisted network configuration (AI configuration services, or AICS). Such AICS may be requested and configured via various messaging and signaling mechanisms. The AI model life cycle management including training, delivery, activation, inference, deactivation, switching, performance evaluation, and the like may be configured, triggered, and otherwise provisioned via control and data messages and signaling communicated between the various network elements in the wireless communication system.

Abstract: Presented are systems and methods for predicting quality of experience of user equipment (UEs) using an artificial intelligence (AI) model. A first network node of a radio access network (RAN) may receive first assistance information for use with a first quality of experience (QoE) information to perform a first function of a neural network model from a second network node of the RAN. The first network node of the RAN may perform the first function using the first QoE information and the first assistance information.

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: A method for supplementary doping of monocrystalline silicon by lowering a device comprising a containing member provided with first and second through-holes are provided. The device includes a hoisting member, a connecting member, and a containing member which are arranged in sequence from top to bottom in a vertical direction, wherein the hoisting member is connected with one end of the connecting member, and another end of the connecting member is movably connected with the containing member, so that the containing member is rotatable with respect to the connecting member. The containing member is provided with a first through-hole and a second through-hole, and the connecting member and the containing member are connected at a joint. A distance between the first through-hole and the joint is less than a distance between the second through-hole and the joint in the vertical direction.

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: This disclosure describes methods and systems for exchanging AI computing information for load prediction model between network elements of a wireless communication network. The methods include: sending, by a first network element of a wireless communication network, a first message for load prediction to a second network element of the wireless communication network, wherein the first message comprises at least one of an input to a machine learning model for load prediction of the first network element or model configuration information of the machine learning model.