Abstract: The invention discloses a method for rendering on the basis of hemispherical orthogonal function, the method comprising the following steps: selecting rendering fragments and establishing a local coordinate system; acquiring a bidirectional reflectance distribution function of a material; if global illumination is an orthogonal function, determining a rotation matrix of an orthogonal function coefficient according to the rotation angles of the global coordinate system and the local coordinate system, and calculating a local orthogonal function illumination coefficient; converting the local orthogonal function illumination coefficient into a hemispherical orthogonal function illumination coefficient; sampling to obtain the spatial distribution of a bidirectional reflection distribution function of a rendered material; obtaining a hemispherical orthogonal function of the bidirectional reflection distribution function of the rendered material; and using the dot product of a hemispherical orthogonal function coef

Abstract: This application provides a wireless communication method and apparatus. The wireless communication method includes: A first device obtains first information, where the first information includes a correspondence between first customer premise equipment and at least one first terminal device, and a correspondence between the first terminal device and at least one second terminal device. The first device configures the first information on a second device, where the first information is used by the second device to verify that a received service packet is a service packet sent by the first terminal device to the second terminal device by using the first customer premise equipment.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle. The high-priority agents can be identified based on a set of mutual importance scores in which each mutual importance score indicates an estimated mutual relevance between the vehicle and a different agent from a set of agents on planning decisions of the other. The mutual importance scores can be calculated based on importance scores assessed from the perspectives of both the vehicle and the agents.

Abstract: An information handling system may include a processor, a touchpad communicatively coupled to the processor, and non-transitory computer-readable media communicatively coupled to the processor and having stored thereon a program of instructions configured to, when read and executed by the processor in response to a trigger for enabling logical segmentation of the touchpad, logically segment the touchpad into a plurality of zones and map each zone to a respective corresponding feature displayed on one or more displays communicatively coupled to the processor such that user interaction with each of the plurality of zones manipulates the respective corresponding feature of such zones on the one or more displays.

Abstract: A refrigeration system and a lubricating method thereof. The refrigeration system (100) includes: a compressor (110), a condenser (120), an evaporator (130), and a lubrication circuit (200), the lubrication circuit including a post-lubrication flow path (230,240,260) connected from the compressor into the condenser and the evaporator respectively; and a pre-lubrication flow path (210,220,250) connected from the condenser and the evaporator into the compressor respectively; wherein after flowing from the condenser via the pre-lubrication flow path to the compressor for lubrication, a part of refrigerant for lubrication can flow back to the evaporator via the post-lubrication flow path; or after flowing from the evaporator via the pre-lubrication flow path to the compressor for lubrication, the part of refrigerant for lubrication can flow back to the condenser via the post-lubrication flow path.

Abstract: To operate an autonomous vehicle, a rail agent is detected in a vicinity of the autonomous vehicle using a detection system. One or more tracks are determined on which the detected rail agent is possibly traveling, and possible paths for the rail agent are predicted based on the determined one or more tracks. One or more motion paths are determined for one or more probable paths from the possible paths, and a likelihood for each of the one or more probable paths is determined based on each motion plan. A path for the autonomous vehicle is then determined based on a most probable path associated with a highest likelihood for the rail agent, and the autonomous vehicle is operated using the determined path.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle and a target agent at a current time point; determine whether the target agent is an emergency vehicle that is active at the current time point; generate from the scene features, an input (i) that includes the scene features and (ii) that indicates whether the target vehicle is an emergency vehicle that is active at the current time point; and process the input using a machine learning model that is configured to generate a behavior prediction output for the target agent that characterizes predicted future behavior of the target agent after the current time point.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining occupancies of surrounding agents. One of the methods includes obtaining scene data characterizing an environment at a current time point; processing a first network input generated from the scene data using a first neural network to generate an intermediate output; obtaining an identification of a future time point that is after the current time point; and generating, from the intermediate output and the future time point, an occupancy output, wherein the occupancy output comprises respective occupancy probabilities for each of a plurality of locations in the environment, wherein the respective occupancy probability for each location characterizes a likelihood that one or more agents will occupy the location at the future time point.

Abstract: The present disclosure relates to zoom lenses and optical devices using the same. A zoom lens may include in order from an object side to an image side: a first lens group, a second lens group, a third lens group, a fourth lens group; and a fifth lens group. The zoom lens may satisfy the following conditions: ?2.28?f2/fw???1.08, and 0.15?TTL/(BFL*fw?)?0.45, wherein f2 denotes a focal length of the second lens group, fw? denotes a focal length of the zoom lens at a wide angle end, TTL denotes a total track length of the zoom lens, and BFL denotes a back focal length of the zoom lens.

Abstract: Processing methods are described that include forming a group of LED structures on a substrate layer to form a patterned LED substrate. The methods also include depositing a light absorption material on the pattered LED substrate, where the light absorption material includes at least one photocurable compound and at least one ultraviolet light absorbing material. The methods further include exposing a portion of the light absorption material to patterned light, wherein the patterned light cures the exposed portion of the light absorption material into pixel isolation structures. The methods additionally include depositing an isotropic layer on a top portion and a side portion of the pixel isolation structures, where the LED structures are substantially free of the as-deposited isotropic light reflecting layer.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode in accordance with behavior predictions for other road users in the vehicle's vicinity. In particular, the vehicle's onboard computing system may predict whether another road user will perform a “continuing” lane driving operation, such as going straight in a turn-only lane. Sensor data from detected/observed objects in the vehicle's nearby environment may be evaluated in view of one or more possible behaviors for different types of objects. In addition, roadway features, in particular whether lane segments are connected in a roadgraph, are also evaluated to determine probabilities of whether other road users may make an improper continuing lane driving operation. This is used to generate more accurate behavior predictions, which the vehicle can use to take alternative (e.g., corrective) driving actions.

Abstract: The present invention discloses a two-step anti-fraud vehicle insurance image collecting and quality testing method, system and device, the method comprises: step 1, collecting vehicle insurance scene images and marking vehicle orientation; step 2, performing object detection on the collected vehicle insurance scene images and screening to obtain object coordinates; step 3, according to the vehicle orientation and the object coordinates, obtaining the specific position of the object coordinates located in the whole vehicle; step 4, according to the object coordinates screened in step 2, performing vehicle component detection on the vehicle insurance scene images, obtaining the component coordinates of the vehicle components, and screening to obtain the vehicle component closest to the object coordinates; step 5, according to the specific position of the object coordinates located in the whole vehicle and the vehicle components closest to the object coordinates, obtaining the position of the vehicle components

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating candidate future trajectories for agents. One of the methods includes obtaining scene data characterizing a scene in an environment at a current time point; for each of a plurality of lane segments, processing a model input comprising (i) features of the lane segment and (ii) features of the target agent using a machine learning model that is configured to process the model input to generate a respective score for the lane segment that represents a likelihood that the lane segment will be a first lane segment traversed by the target agent after the current time point; selecting, as a set of seed lane segments, a proper subset of the plurality of lane segments based on the respective scores; and generating a plurality of candidate future trajectories for the target agent.

Abstract: Provided is a two-stage self-organizing optimized aggregation method and system for distributed resources of a virtual power plant.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode in accordance with behavior predictions for other road users in the vehicle's vicinity. In particular, the vehicle's onboard computing system may predict whether another road user will perform a “continuing” lane driving operation, such as going straight in a turn-only lane. Sensor data from detected/observed objects in the vehicle's nearby environment may be evaluated in view of one or more possible behaviors for different types of objects. In addition, roadway features, in particular whether lane segments are connected in a roadgraph, are also evaluated to determine probabilities of whether other road users may make an improper continuing lane driving operation. This is used to generate more accurate behavior predictions, which the vehicle can use to take alternative (e.g., corrective) driving actions.

Abstract: Jaywalking behaviors of vulnerable road users (VRUs) such as cyclists or pedestrians can be predicted. Location data is obtained that identifies a location of a VRU within a vicinity of a vehicle. Environmental data is obtained that describes an environment of the VRU, where the environmental data identifies a set of environmental features in the environment of the VRU. The system can determine a nominal heading of the VRU, and generate a set of predictive inputs that indicate, for each of at least a subset of the set of environmental features, a physical relationship between the VRU and the environmental feature. The physical relationship can be determined with respect to the nominal heading of the VRU and the location of the VRU. The set of predictive inputs can be processed with a heading estimation model to generate a predicted heading offset (e.g., a target heading offset) for the VRU.

Abstract: The present invention discloses a preprocessing and imputing method for structural data, comprising: step 1, querying the missing information of an original data, counting missing values, and obtaining a missing rate for the original data; step 2, based on the missing rate, performing listwise deletion on the original data, and then traversing the rows to generate corresponding dichotomous arrays, converting the arrays to the form of histogram, calculating the maximum rectangular area formed by the corresponding histogram, and then sorting all rectangular areas to obtain the maximum complete information matrix; step 3, using multiple imputation by chained equations, auto-encoders, or generative adversarial imputation networks to impute missing values on the original data.

Abstract: To operate an autonomous vehicle, a rail agent is detected in a vicinity of the autonomous vehicle using a detection system. One or more tracks are determined on which the detected rail agent is possibly traveling, and possible paths for the rail agent are predicted based on the determined one or more tracks. One or more motion paths are determined for one or more probable paths from the possible paths, and a likelihood for each of the one or more probable paths is determined based on each motion plan. A path for the autonomous vehicle is then determined based on a most probable path associated with a highest likelihood for the rail agent, and the autonomous vehicle is operated using the determined path.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining respective importance scores for a plurality of agents in a vicinity of an autonomous vehicle navigating through an environment. The respective importance scores characterize a relative impact of each agent on planned trajectories generated by a planning subsystem of the autonomous vehicle. In one aspect, a method comprises providing different states of an environment as input to the planning subsystem and obtaining as output from the planning subsystem corresponding planned trajectories. Importance scores for the one or more agents that are in one state but not in the other are determined based on a measure of difference between the planned trajectories.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle and, for only those agents which are high priority agents, generating data characterizing the agents using a first prediction model. In a first aspect, a system identifies multiple agents in an environment in a vicinity of a vehicle. The system generates a respective importance score for each of the agents by processing a feature representation of each agent using an importance scoring model. The importance score for an agent characterizes an estimated impact of the agent on planning decisions generated by a planning system of the vehicle which plans a future trajectory of the vehicle. The system identifies, as high-priority agents, a proper subset of the plurality of agents with the highest importance scores.