Abstract: A system for real-time control selection and calibration in a vehicle using a deep-Q network (DQN) includes sensors and actuators disposed on the vehicle. A control module has a processor, memory, and input/output (I/O) ports in communication with the one or more sensors and the one or more actuators. The processor executes program code portions that cause the sensors actuators to obtain vehicle dynamics and road surface estimation information and utilize the vehicle dynamics information and road surface estimation information to generate a vehicle dynamical context. The system decides which one of a plurality of predefined calibrations is appropriate for the vehicle dynamical context, generates a command to the actuators based on a selected calibration. The system continuously and recursively causes the program code portions to execute while the vehicle is being operated.

Abstract: A perception system is adapted to receive visual data from a camera and includes a controller having a processor and tangible, non-transitory memory on which instructions are recorded. A subsampling module, an object detection module and an attention module are each selectively executable by the controller. The controller is configured to sample an input image from the visual data to generate a rescaled whole image frame, via the subsampling module. The controller is configured to extract feature data from the rescaled whole image frame, via the object detection module. A region of interest in the rescaled whole image frame is identified, based on an output of the attention module. The controller is configured to generate a first image based on the rescaled whole image frame and a second image based on the region of interest, the second image having a higher resolution than the first image.

Abstract: Presented are embedded control systems with logic for computation and data sharing, methods for making/using such systems, and vehicles with distributed sensors and embedded processing hardware for provisioning automated driving functionality. A method for operating embedded controllers connected with distributed sensors includes receiving a first data stream from a first sensor via a first embedded controller, and storing the first data stream with a first timestamp and data lifespan via a shared data buffer in a memory device. A second data stream is received from a second sensor via a second embedded controller. A timing impact of the second data stream is calculated based on the corresponding timestamp and data lifespan. Upon determining that the timing impact does not violate a timing constraint, the first data stream is purged from memory and the second data stream is stored with a second timestamp and data lifespan in the memory device.

Abstract: The preset application discloses a task scheduling method, including: in response to receiving an issued task, dividing, by a parser, the task into sub-tasks and generating a sub-task list, a task parameter corresponding to each sub-task is recorded in the sub-task list, the task parameter includes a start phase of a next sub-task; sending, by a scheduler, the task parameter of a sub-task to be processed in the sub-task list to a corresponding sub-engine; executing, by the corresponding sub-engine, a corresponding sub-task to be processed; sending a notification to the scheduler in response to an operating phase when the corresponding sub-engine executes the corresponding sub-task to be processed being the same as the start phase in the received task parameter; and in response to the notification being detected by the scheduler, returning to the step of sending the task parameter of a sub-task to be processed to a corresponding sub-engine.

Abstract: A method includes receiving sensed vehicle-state data, actuation-command data, and surface-coefficient data from a plurality of remote vehicles, inputting the sensed vehicle-state data, the actuation-command data, and the surface-coefficient data into a self-supervised recurrent neural network (RNN) to predict vehicle states of a host vehicle in a plurality of driving scenarios, and commanding the host vehicle to move autonomously according to a trajectory determined using the vehicle states predicted using the self-supervised RNN.

Abstract: A method for determining a lane centerline includes detecting a remote vehicle ahead of a host vehicle includes determining a trajectory of the remote vehicle that is ahead of the host vehicle, extracting features of the trajectory of the remote vehicle that is ahead of the host vehicle to generate a trajectory feature vector, and classifying the trajectory of the remote vehicle that is ahead of the host vehicle using the trajectory feature vector to determine whether the trajectory of the remote vehicle includes a lane change. The method further includes determining a centerline of the current lane using the trajectory of the remote vehicle that does not include the lane change and commanding the host vehicle to move autonomously along the centerline of the current lane to maintain the host vehicle in the current lane.

Abstract: A method includes receiving sensed vehicle-state data, actuation-command data, and surface-coefficient data from a plurality of remote vehicles, inputting the sensed vehicle-state data, the actuation-command data, and the surface-coefficient data into a self-supervised recurrent neural network (RNN) to predict vehicle states of a host vehicle in a plurality of driving scenarios, and commanding the host vehicle to move autonomously according to a trajectory determined using the vehicle states predicted using the self-supervised RNN.

Abstract: A method of modeling precipitation effects in a virtual LiDAR sensor, the method includes receiving a point cloud model representing three-dimensional coordinates of objects as the objects would be sensed by a LiDAR sensor. The method further includes generating a stochastic model of rainfall or snowfall, estimating a probability that a light source from the LiDAR sensor hits a raindrop or a snowflake based on the stochastic model, and modifying the received point cloud model to include effects induced by the modeled rainfall or snowfall based on the probability that light sourced from the LiDAR sensor encounters a raindrop or a snowflake.

Abstract: The present disclosure provides the use of BAZ1B_K426hy in the preparation of a product for tumor detection and belongs to the field of biotechnology. The present disclosure further provides a group of immunogenic polypeptides, including polypeptide A and polypeptide B. An anti-BAZ1B_K426hy polyclonal antibody is prepared by conducting mixed immunization on an animal with the immunogenic polypeptide. The polyclonal antibody can specifically recognize an endogenous protein BAZ1B_K426hy by enzyme-linked immunosorbent assay (ELISA)/Dot blot/Western blot, which is used for preparation of detection products for tumors and Williams syndrome.

Abstract: A base station can select orthogonal frequency-division multiplexing (OFDM) numerologies that define subcarrier spacing values based on attributes associated with one or more services that a user equipment (UE) is using. The base station can use the selected OFDM numerologies for transmission associated with the services. When the UE is using multiple services simultaneously, the base station can select the same or different OFDM numerologies for the multiple services.

Abstract: A dynamic side blind zone method includes determining that a host vehicle is approaching a first lane that is nonparallel to a second lane. The host vehicle is moving in the second lane. The method further includes activating an adaptive side blind zone alert system of the host vehicle in response to determining that the host vehicle is approaching the first lane that is nonparallel to the second lane, determining a warning zone in response to activating the adaptive side blind zone alert system of the host vehicle, and detecting a remote vehicle inside the warning zone after determining the warning zone. The remote vehicle is moving in the first lane. The method further includes providing an alert to a vehicle user of the host vehicle in response to detecting that the remote vehicle is inside the warning zone.

Abstract: A capacitance detection apparatus and an electronic device are disclosed. The capacitance detection apparatus includes: a sensing module, a connecting circuit, and a differential detection circuit for detecting changes in capacitance of the sensing module; the sensing module comprises: a substrate, and a first sensing layer and a second sensing layer respectively located on two sides of the substrate; a first sensing unit of the first sensing layer is opposite to a second sensing unit of the second sensing layer, and the first sensing unit covers the second sensing unit; the first sensing unit and the second sensing unit are electrically connected to the differential detection circuit. When a detection object approaches the capacitance detection apparatus, the capacitance of the first sensing unit is influenced by the temperature and the detection object, and the capacitance of the second sensing unit is only influenced by the temperature.

Abstract: A virtual LiDAR sensor system fora motor vehicle includes a plurality of camera modules and algorithms that generate a depth image, a RGB image, and a segmentation information image. The system is implemented with an algorithm that associates the backscattered signals with information from a color-reflectivity table, incident angle determination and depth information.

Abstract: A slice manager associated with a network access point of a telecommunication network can manage combinations of network slices and bandwidth parts for user equipment (UE). The bandwidth parts can have independently set numerologies, such as subcarrier spacing values. The UE can be configured to use one or more active bandwidth parts at a time, such that the slice manager can instruct the UE to use multiple active bandwidth parts simultaneously with respect to the same network slice or multiple network slices.

Abstract: An automobile vehicle continuous validation system includes a backend collecting data from a vehicle fleet and wirelessly communicating with the vehicle fleet. The backend is in wireless communication with at least one client. A vehicle module is provided on-board individual ones of multiple automobile vehicles of the vehicle fleet and performing an on-board vehicle validation analysis. A fleet-based validation module provided either at the backend or cloud based manages data defining a configuration of and a capability of the multiple automobile vehicles of the vehicle fleet. A validation manager generates validation tasks based on a user's definition or a desired production of the validation tasks of the validation analysis and a fleet vehicle availability. A client-side module remote from the multiple automobile vehicles of the vehicle fleet has interface items applied by the at least one client seeking to perform the validation analysis.

Abstract: Disclosed are a sealed box container, a main machine of a heat recovery switching device and a refrigeration device. The sealed box container includes box bodies that are spliced to form a sealed cavity, and is provided with a through hole in communication with the sealed cavity, and the sealed cavity is used for accommodating a pipeline assembly of a main machine, and the pipeline assembly is connected to an external pipeline by means of the through hole.

Abstract: Various systems, methods, and devices relate to determining a delay associated with a device; calculating a guard time based at least in part on the delay; and scheduling a wireless resource to include a downlink interval, an uplink interval, and the guard time between the downlink interval and the uplink interval. By calculating the guard time based at least in part on the delay associated with the device, spectrum efficiency can be enhanced, and latency can be reduced.

Abstract: A vehicle system includes a lidar system that obtains an initial point cloud and obtains a dual density point cloud by implementing a first neural network and based on the initial point cloud. The dual density point cloud results from reducing point density of the initial point cloud outside a region of interest (ROI). Processing the dual density point cloud results in a detection result that indicates any objects in a field of view (FOV) of the lidar system. A controller obtains the detection result from the lidar system and controls an operation of the vehicle based on the detection result.

Abstract: A base station can select orthogonal frequency-division multiplexing (OFDM) numerologies that define subcarrier spacing values based on attributes associated with one or more services that a user equipment (UE) is using. The base station can use the selected OFDM numerologies for transmission associated with the services. When the UE is using multiple services simultaneously, the base station can select the same or different OFDM numerologies for the multiple services.