Abstract: An example operation includes one or more of determining a condition at a location containing a past occupant of a vehicle, determining a time when the past occupant will become an occupant of the vehicle, and adjusting another condition of a cabin of the vehicle to be at the condition at the time.

Abstract: An example operation includes one or more of analyzing data related to content being delivered to occupant devices in a vehicle; and notifying the devices of additional functionality related to the vehicle based on the analyzing.

Abstract: Example methods and apparatuses are described. An example method includes: receiving first physical uplink control channel (PUCCH) configuration information corresponding to a first service and second PUCCH configuration information corresponding a second service, and respectively indicate a granularity of a first time unit and a granularity of a second time unit; determining first hybrid automatic repeat request (HARQ) information and second HARQ information, where a priority of the first HARQ information is the same as a priority of the second HARQ information; and in response to determining that the granularity of the first time unit is different from the granularity of the second time unit, feeding back the first HARQ information in the first time unit and the second HARQ information in the second time unit, wherein the first time unit and the second time unit do not overlap in time domain.

Abstract: A channel state information measurement method includes receiving, by a terminal device, configuration information from a network device. The configuration information includes first indication information and second indication information. The first indication information indicates K channel measurement signal resources, K is greater than or equal to 2, the second indication information indicates the terminal device is to measure aggregated channel state information (CSI) based on N channel measurement signal resources, and N is less than or equal to K. The method also includes measuring, by the terminal device, the N channel measurement signal resources based on the configuration information. The method further includes obtaining, by the terminal device, the aggregated CSI through calculation based on N measurement results. The aggregated CSI is CSI of M antenna ports, and M is a sum of quantities of antenna ports of the N channel measurement signal resources.

Abstract: Embodiments of this application provide a communication method and a related device. The method includes: A terminal device obtains a plurality of power offset values corresponding to one reference signal resource, determines a plurality of pieces of channel state information CSI based on the plurality of offset values, and sends some or all of the plurality of pieces of CSI to a network device. The network device may flexibly adjust data transmit power based on the plurality of power offset values and the plurality of pieces of corresponding CSI, and perform appropriate link adaptation adjustment.

Abstract: An example operation includes recording, from a vehicle sensor, data indicative of a plurality of movements of a first occupant in an interior of a vehicle; determining, from the recording, a first maximum range of extension among the plurality of movements, and a first amount of time between a first movement and a second movement of the plurality of movements; and assigning the first occupant to one of a plurality of age groups, based upon the determining.

Abstract: A picture annotation method includes starting an annotation tool to recognize a hierarchical relationship between candidate layers in the annotation tool; acquiring an annotation event of a picture to be annotated; distributing the annotation event to at least one target master candidate layer based on the hierarchical relationship; distributing, for an arbitrary target master candidate layer, in the case where the arbitrary target master candidate layer is configured with a slave candidate layer, starting from the arbitrary target master candidate layer, the annotation event down level by level to target slave candidate layers of at least one level of the arbitrary target master candidate layer; processing the annotation event through a first target candidate layer, to which it is distributed.

Abstract: An example operation includes one or more of determining a movement of an occupant in a vehicle, determining an atypical health condition based on the movement and a position of the occupant in the vehicle, determining if the occupant is breathing, based on an analysis performed by the vehicle, verifying the atypical health condition by the vehicle, based on received data from a device proximate the occupant, and sending a notification to an entity, based on the verification.

Abstract: An example operation includes one or more of receiving a call on a device associated with an occupant of a vehicle, determining a noise level proximate the occupant, and directing the call to a speaker proximate the occupant, based on the noise level.

Abstract: Disclosed is a method for training an expression transfer model performed by a computer device, the method including: obtaining a source domain facial image of a first object, a target domain facial image of a second object and a facial feature image associated with the target domain facial image; applying the facial feature image and the source domain facial image to an expression transfer model to obtain a synthesized facial image of the first object; applying the synthesized facial image and the target domain facial image to a discriminative network model obtain two discrimination results; applying the synthesized facial image and the target domain facial image to an image classification model to obtain a category feature vector for identifying a difference between the synthesized facial image and the target domain facial image; and updating the expression transfer model according to the category feature vector and the discrimination results.

Abstract: Embodiments of the disclosure provide a method and an apparatus for sharing data across groups. In one embodiment, the method comprises creating, by a cross-group collaboration platform, a collaboration project; determining, by the cross-group collaboration platform, groups participating in the collaboration project to designate the groups as project collaborators for the collaboration project; and sharing, by the cross-group collaboration platform, collaboration data amongst the project collaborators of the collaboration project.

Abstract: An example operation includes one or more of receiving a scan of a cabin of a vehicle, wherein the scan includes a spatial region inside the vehicle and outside the vehicle proximate at least one vehicle door, determining at least one occupant characteristic based on the scan, including a classification detection and a presence detection of at least one seat inside the vehicle, determining a cabin status based on the at least one occupant characteristic and communicating the cabin status to a mobile device.

Abstract: An embodiment of this application discloses an artificial intelligence-based image generation method performed by a computer device. The method includes: acquiring a source image including a target object whose pose is to be transformed, and a target image including a reference object presenting a target pose; determining a pose transition matrix according to a model pose corresponding to the pose of the target object and a model pose corresponding to the target pose of the reference object; extracting a basic appearance feature of the target object from the source image; processing the basic appearance feature based on the pose transition matrix, to obtain a target appearance feature of the target object in the target pose; and generating a target synthetic image of the target object in the target pose based on the target appearance feature.

Abstract: An example operation includes one or more of entering, by a vehicle, a security mode, when sensors on the vehicle detect a movement or an irregular sound, collecting data, by the vehicle, from the sensors to record an area proximate the vehicle, analyzing, by the vehicle, the data to determine a security threat, notifying, by the vehicle, a device associated with the vehicle when the security threat is above a threshold, and performing an action, by the vehicle, based on a message received from the device.

Abstract: A SONOS structure, a method for erasing the SONOS structure, and a method for programming the SONOS structure are provided. The SONOS structure includes a semiconductor substrate, a dielectric layer disposed on the semiconductor substrate, a charge trapping layer disposed on the dielectric layer, a tunneling dielectric layer covering the charge trapping layer, and a conductive layer disposed on the tunneling dielectric layer. A thickness of the dielectric layer is greater than a thickness of the tunneling dielectric layer.

Abstract: Provided is a process that includes one or more of receiving data from sensors on a vehicle, where the data is associated with an internal environment of the vehicle and characteristics of an occupant of the vehicle and modifying functionality of the vehicle based on the received data, where the modifying updates a Graphical User Interface (GUI) of the vehicle and a GUI of a device associated with the occupant.

Abstract: An example operation includes one or more of determining one or more objects in a transport that may become airborne and altering a portion of the transport to minimize the one or more objects from becoming airborne during a collision.

Abstract: A rubber and metal composite electric contact and a preparation process therefor. The rubber and metal composite electric contact is a circular layered complex which is formed by tightly combining a metal sheet layer having a plurality of through holes and a rubber layer by means of thermal vulcanization molding and which has a thickness of 0.1 to 5 mm and a diameter of 1 to 15 mm. There is no isolation layer between the rubber layer and the metal layer of the electric contact, so no rubber overflows the outer surface of the metal layer. In the rubber and metal composite electric contact, the rubber and metal are combined firmly and the overall strength of the electric contact is adjustable; the electric contact also has good dust resistance; and the electric contact thus has stable and reliable electrical conductivity.

Abstract: An example operation includes one or more of receiving a scan of a cabin of a vehicle, wherein the scan includes a spatial region inside the vehicle and outside the vehicle proximate at least one vehicle door, determining at least one occupant characteristic based on the scan, including a classification detection and a presence detection of at least one seat inside the vehicle, determining a cabin status based on the at least one occupant characteristic and communicating the cabin status to a mobile device.

Abstract: A substation oil sampling robot comprises a smart mobile component, a robot arm grasping member, auxiliary sampling components, and auxiliary sampling platform components. The robot arm grasping member comprises a robot arm body fixedly mounted on the smart mobile component and a robot gripper unit. The auxiliary sampling components comprise sample bottles and a valve opening and closing tool, and the robot gripper unit is arranged with a first gripping portion matched with the sample bottles and a second gripping portion matched with the valve opening and closing tool. The sampling platform components comprise an auxiliary sampling tool connected with the pipeline. The pipeline is arranged with a pipeline valve. The auxiliary sampling tool comprises an auxiliary valve, an auxiliary sampling piping component, and an auxiliary sampling piping component support, and the outlet of the pipeline valve is in communication with the inlet of the auxiliary sampling piping component.