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: 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.

Abstract: An example operation includes detecting, by a vehicle, a location of a first potential passenger proximate to a road; determining, by the vehicle, a first road safety level of a pick-up for the first potential passenger; denying, by the vehicle, the pick-up for the first potential passenger when the determined first road safety level is below a threshold; determining, by the vehicle, a second road safety level of a pick-up for a second potential passenger; and picking up, by the vehicle, the second potential passenger, when the second road safety level is above the threshold.

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: 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. Modifying functionality includes updating a graphical user interface (GUI) of the vehicle and a GUI of a device associated with the occupant.

Abstract: Techniques associated with exchanging data between clusters are disclosed. A data packet can be received from a first pod in a first cluster of a cluster set that targets a second pod or service in a second cluster of the cluster set. A label identity is determined for the first pod from a table of pods and label identities. The label identity for the first pod is added in a virtual network identifier field of a data packet header. The data packet is communicated from a first virtual switch to the second cluster through a tunnel interface and gateway node. Upon receipt of the data packet, the label identity is extracted from the data packet header, and an ingress rule associated with the label identity can be determined. Access to the second pod is controlled based on the rule.

Abstract: The present invention relates to an outdoor unit for a refrigeration cabinet and a refrigeration cabinet. The outdoor unit comprises: a first unit comprising a compressor; a second unit comprising a condenser; wherein, the outdoor unit is configured to be installed in a first mode or a second mode; where in the first mode, the first unit and the second unit are installed adjacent to each other and connected with each other through fasteners, and the first unit and the second unit are connected through a first fluid pipeline passing through an adjacent surface between the first unit and the second unit; where in the second mode, the first unit and the second unit are respectively installed at a first position and a second position spaced apart, and the first unit and the second unit are connected through a second fluid pipeline extending between the first and second positions.

Abstract: An example operation includes one or more of detecting a movement of an object in a vehicle when the vehicle is in motion, and determining that the object is an inanimate object, based on a vertical and horizontal distance of the detected movement.

Abstract: An example operation includes one or more of determining a level of risk of a collision of a transport, wherein the level of risk is related to an occupant of the transport and an environment of the transport, accumulating an amount of data based on the level of risk, preparing the accumulated data for sending to one or more recipients when the level of risk exceeds a risk threshold, and sending the prepared data to the one or more recipients when the collision occurs.

Abstract: An example operation includes one or more of detecting a living element in a transport, determining a dangerous condition exists in response to an internal temperature of the transport is outside of a threshold and a negative characteristic is associated with the living element, and positioning the transport to a location to reduce the dangerous condition.