Abstract: A method for controlling liquid ingress detection and an electronic device are provided. The method includes: controlling a liquid ingress detection circuit to start liquid ingress detection in a Type-C interface; stopping applying a voltage to first data pins when a detection result of the liquid ingress detection is that liquid ingress occurs in the Type-C interface, and obtaining a first parameter of a screen of the electronic device; when the first parameter of the screen is a screen-off state, controlling the liquid ingress detection circuit to start next liquid ingress detection in the Type-C interface after first duration; and when the first parameter of the screen is a screen-on state, controlling the liquid ingress detection circuit to start next liquid ingress detection in the Type-C interface after second duration, where the first duration is greater than the second duration.

Abstract: A camera view share system is provided. The camera view share system includes a road-side unit. The road-side unit includes a controller configured to receive a request for a bird-eye-view map from an ego vehicle, the bird-eye-view map including a plurality of vehicles, transmit the bird-eye-view map to the ego vehicle, receive a selection of a target vehicle among the plurality of vehicles from the ego vehicle, and transmit a camera feed related to the target vehicle to the ego vehicle.

Abstract: A system for communication-aware federated learning includes a server and edge nodes. Each of the edge nodes trains a machine learning model using first local data obtained by sensors of corresponding edge node. Each of the edge nodes obtains network bandwidth for a channel between corresponding edge node and the server. One or more of the edge nodes determines a level of compression based on the bandwidth for the channel, compresses the trained machine leaning model based on the determined level of compression, and transmits the compressed trained machine learning model to the server. The server decompresses the compressed trained machine learning models and aggregates the decompressed trained machine learning models to obtain the aggregated machine learning model, and transmits the aggregated machine learning model to each of the edge nodes. Each of the edge nodes receives the aggregated machine learning model from the server.

Abstract: Various embodiments herein are directed to beamforming associated with multiple-input multiple-output (MIMO) modes in open radio access network (O-RAN) systems. In one embodiment, an apparatus comprises: memory to store beamforming configuration information associated with a plurality MIMO modes; and processing circuitry, coupled with the memory to: retrieve the beamforming configuration information from the memory; request, based on the beamforming configuration information, measurements associated with the plurality of MIMO modes; receive the measurements associated with the plurality of MIMO modes; and based on the received measurements, train an artificial intelligence/machine learning (AI/ML) model that is to predict relative beamforming performance between the plurality of MIMO modes.

Abstract: This disclosure describes systems, methods, and devices related to enhanced measurement reporting. The device may generate radio access network (RAN) measurement parameters to configure an E2 node in Open Radio Access Network (O-RAN). The device may transmit an action definition to the E2 node through an E2 interface, wherein the action definition comprises a measured value reporting conditions information element (IE) based on the RAN measurement parameters, indicating to the E2 node to generate measurement reports. The device may identify the measurement reports received from the E2 node.

Abstract: A system for contribution-aware federated learning is provided. The system includes a server and a plurality of vehicles. Each of the plurality of vehicles includes a controller programmed to: train a local machine learning model using first local data; obtain metadata for hardware elements of corresponding vehicle; transmit the trained local machine learning model and the metadata to a server; receive an aggregated machine learning model from the server; and train the aggregated machine learning model using second local data. The server generates the aggregated machine learning model based on the trained local machine learning models and the metadata received from the plurality of vehicles.

Abstract: An edge device for providing an HD map to a vehicle is provided. The edge device includes a controller programmed to obtain an HD map request including a task type from a vehicle, obtain a status of a wireless channel between the vehicle and the edge device, determine an HD map version among a plurality of versions based on the status of the wireless channel and the task type, and transmit the determined HD map version to the vehicle.

Abstract: The disclosed system for loading and unloading the substrate includes: a substrate rotation apparatus having a first rotation position and a second rotation position with a difference in rotation angle of 90 degrees, wherein the substrate rotation apparatus includes two layers of sucker assemblies, each of which includes a plate body, a plurality of support suction tubes arranged on the plate body, and first suckers connected with tops of respective support suction tubes respectively, and there are gaps, for inserting the substrate therein, between respective first suckers of a lower layer of sucker assembly, and a plate body of an upper layer of sucker assembly; and a mechanical hand including a plurality of mechanical fingers capable of holding two halves of the substrate, both of which are arranged in a length direction of the mechanical fingers, and joined together into an entire substrate.

Abstract: The disclosed system for loading and unloading the substrate includes: a substrate rotation apparatus having a first rotation position and a second rotation position with a difference in rotation angle of 90 degrees, wherein the substrate rotation apparatus includes two layers of sucker assemblies, each of which includes a plate body, a plurality of support suction tubes arranged on the plate body, and first suckers connected with tops of respective support suction tubes respectively, and there are gaps, for inserting the substrate therein, between respective first suckers of a lower layer of sucker assembly, and a plate body of an upper layer of sucker assembly; and a mechanical hand including a plurality of mechanical fingers capable of holding two halves of the substrate, both of which are arranged in a length direction of the mechanical fingers, and joined together into an entire substrate.