Abstract: A substrate for epitaxial growth includes a central region that has a center of the substrate and that serves as a non-modified region, and a peripheral region that surrounds the central region in a manner to be spaced apart from the center of the substrate by a distance and that serves as a modified region having a plurality of modified points. A method for manufacturing a substrate for epitaxial growth includes providing a substrate and forming a plurality of modified points in an interior of the substrate in position corresponding to the modified region. A semiconductor device including the substrate and a method for manufacturing the semiconductor device are also disclosed.

Abstract: A computer-implemented method for aligning a sensor to a vehicle includes receiving a first frame of measurement from the sensor which includes a first point cloud. One or more clusters Ci representing one or more objects or the ground are segmented. A first set of feature vectors fi is computed for each cluster Ci. Based on the first set of feature vectors fi a second set of feature vectors fi? is predicted respectively using an initial transformation. A third set of feature vectors fj is computed for a second frame with a second point cloud with clusters Cj. A pair of matching clusters is identified from Ci and Cj. A feature distance between the matching clusters is computed. An alignment transformation is computed by updating the initial transformation based on the feature distance. The method further includes aligning the sensor and the vehicle based on the alignment transformation.

Abstract: The present disclosure provides a resource allocation method and apparatus, a readable medium and an electronic device. The method includes: acquiring a target resource type corresponding to a target task; acquiring a plurality of resource types of a target processor, wherein each resource type corresponds to one or more virtual processor resources of the target processor; determining a specified resource type that is identical to the target resource type from the plurality of resource types; determining a target processor resource from one or more virtual processor resources corresponding to the specified resource type; and allocating the target processor resource to the target task.

Abstract: A touch panel, a display panel, and a display device. The touch panel includes: a substrate; an electrode layer disposed on the substrate. The electrode layer includes a plurality of second electrodes and a plurality of first electrodes arranged to intersect with the second electrodes; and an insulating layer. The second electrodes and the first electrodes are insulated by the insulating layer, and the insulating layer includes an inorganic material layer and an organic material layer. The inorganic material layer is provided with openings at least corresponding to intersections of the second electrodes and the first electrodes, and a part of the organic material layer fills in the openings.

Abstract: A displaying base plate and a manufacturing method thereof, and a displaying device. The displaying base plate includes a substrate, and a first electrode layer disposed on one side of the substrate, wherein the first electrode layer includes a first electrode pattern; a first planarization layer disposed on one side of the first electrode layer that is away from the substrate, wherein the first planarization layer is provided with a through hole, and the through hole penetrates the first planarization layer, to expose the first electrode pattern; and a second electrode layer, a second planarization layer and a third electrode layer that are disposed in stack on one side of the first planarization layer that is away from the substrate, wherein the second electrode layer is disposed closer to the substrate, the second electrode layer is connected to the first electrode pattern and the third electrode layer.

Abstract: A computer-implemented method for aligning a sensor to reference coordinate system includes initiating a plurality of threads, each thread executes simultaneously and independent of each other. A first thread parses data received from the sensor and stores the parsed data in a data buffer. A second thread computes an alignment transformation using the parsed data to determine alignment between the sensor and the reference coordinate system. The computing includes checking that the data buffer contains at least predetermined amount of data. If at least the predetermined amount of data exists, an intermediate result is computed using the parsed data in the data buffer; otherwise, the second thread waits for the first thread to add more data to the data buffer. The second thread outputs the intermediate result into the data buffer. A third thread outputs the alignment transformation, in response to completion of alignment computations.

Abstract: A vehicle includes a system performing a method of operating a camera for the vehicle. The camera is configured to capture an image. The processor is configured to query the camera to obtain an intrinsic parameter of the camera, estimate a unified parameter based on the intrinsic parameter of the camera, and perform at least one application on the image using the unified parameter.

Abstract: A neural network optimization method includes receiving a model file of a to-be-optimized neural network; obtaining a search space of a target neural network architecture based on the model file of the to-be-optimized neural network, where the search space includes a value range of each attribute of each neuron in the target neural network architecture; obtaining the target neural network architecture based on the search space; training the target neural network architecture based on the model file of the to-be-optimized neural network, to obtain a model file of a target neural network; and providing the model file of the target neural network to a user.

Abstract: The present disclosure relates to a method and system for multi-source algae image target detection, and relates to the field of monitoring of algal bloom events in fresh water. The method includes first crawling images of algae of a selected species by using a built automated algae crawling tool, where the images include all formats; classifying and labeling algae in the algae images, and forming a source domain dataset by using all the classified and labeled algae images; performing transfer learning by using a faster recurrent revolutional neural network (Faster RCNN) with reference to a target domain dataset, to obtain a multi-source algae image target detection model; and finally performing identification and classification by using the multi-source algae image target detection model.

Abstract: A vehicle, a system and a method of navigating the vehicle. The system includes a camera conveyed by the vehicle and a processor. The camera is configured to obtain an original image data file of an environment. The processor is configured to reduce the original image data file to obtain a reduced image data file and determine an alignment between a camera-centered coordinate system and a ground coordinate system using the reduced image data file.

Abstract: A patterned substrate includes a substrate body having a surface and a plurality of patterned structures periodically arranged on the surface of the substrate body, where each of the patterned structures includes a first portion formed on the surface of the substrate body, and a second portion formed on the first portion, and where any two adjacent ones of the patterned structures are spaced apart from one another by a minimum distance of not greater than 0.1 ?m. A light-emitting diode includes the patterned substrate and a semiconductor epitaxial structure formed thereon. A process for preparing the patterned substrate and a process for preparing the light-emitting diode are also disclosed.

Abstract: Systems and methods for a vehicle are provided. In one embodiment, a method includes: receiving image data defining a plurality of images associated with an environment of the vehicle; receiving vehicle data indicating a velocity of the vehicle, wherein the vehicle data is associated with the image data; determining, by a processor, feature points within at least one image based on the vehicle data and a three dimensional projection method; selecting, by the processor, a subset of the feature points as ground points; determining, by the processor, a ground plane based on the subset of feature points; determining, by the processor, a ground normal vector from the ground plane; determining, by the processor, a camera to ground alignment value based on the ground normal vector; and generating, by the processor, second image data based on the camera to ground alignment value.

Abstract: Systems and methods for a vehicle are provided. In one embodiment, a method includes: receiving image data defining a plurality of images associated with an environment of the vehicle; determining, by a processor, feature points within at least one image of the plurality of images; selecting, by the processor, a subset of the feature points as ground points based on a fixed two dimensional image road mask and a three dimensional region; determining, by the processor, a ground plane based on the subset of feature points; determining, by the processor, a ground normal vector from the ground plane; determining, by the processor, a camera to ground alignment value based on the ground normal vector; and generating, by the processor, second image data based on the camera to ground alignment value.

Abstract: Methods and systems for a vehicle are provided. In one embodiment, the method includes: receiving image data defining a plurality of images associated with an environment of the vehicle; determining, by a processor, feature points within at least one image of the plurality of images; selecting, by the processor, a subset of the feature points as ground points; determining, by the processor, a ground plane based on the subset of feature points; determining, by the processor, a ground normal vector from the ground plane; determining, by the processor, the ground normal vector based on a sliding widow method; determining, by the processor, a camera to ground alignment value based on the ground normal vector; and generating, by the processor, second image data based on the camera to ground alignment value.

Abstract: A vehicle control system including a spatial monitoring system includes on-vehicle cameras that capture images, from which are recovered a plurality of three-dimensional (3D) points. A left ground plane normal vector is determined for a left image, a center ground plane normal vector is determined for a front image, and a right ground plane normal vector is determined for a right image. A first angle difference between the left ground plane normal vector and the center ground plane normal vector is determined, and a second angle difference between the right ground plane normal vector and the center ground plane normal vector is determined. An uneven ground surface is determined based upon one of the first angle difference or the second angle difference, and an alignment compensation factor for the left camera or the right camera is determined. A bird's eye view image is determined based upon the alignment compensation factor.

Abstract: A system for on-vehicle camera alignment monitoring includes an on-vehicle camera in communication with a controller. The controller monitors vehicle operating parameters and camera signal parameters, and captures an image file from the on-vehicle camera. A first level analysis of the image file, the vehicle operating parameters, and the camera signal parameters is executed to detect dynamic conditions and image feature parameters that affect camera alignment. An error with one of the dynamic conditions or the image feature parameters that affects the camera alignment is detected. A second level analysis of the camera signal parameters is executed to identify a root cause indicating one of the dynamic conditions or the image feature parameters that affects the camera alignment based upon the error. A camera alignment-related fault is detected based upon the root cause, and vehicle operation is controlled based upon the camera alignment-related fault.

Abstract: For processing cost reduction and improvement of efficiency, a no-mold-runner multi-nozzle device, comprising: an injection machine, a multi-nozzle component, a front template, and a no-mold-runner. The multi-nozzle component includes a plurality of nozzles, which is connected to the injection machine. The injection machine is used to inject a mixture of molding material and supercritical fluid into multiple nozzles. The front template is provided with a plurality of first passage holes. The no-mold-runner is provided with a mold cavity and a plurality of second passage holes communicating with the mold cavity. The nozzle correspondingly passes through a plurality of first passage holes and second passage holes and is installed in cooperation. By controlling the opening or closing of the nozzle, the mixed material of the molding material and the supercritical fluid enters the mold cavity or stops entering the mold cavity.

Abstract: A substrate for epitaxial growth includes a central region that has a center of the substrate and that serves as a non-modified region, and a peripheral region that surrounds the central region in a manner to be spaced apart from the center of the substrate by a distance and that serves as a modified region having a plurality of modified points. A method for manufacturing a substrate for epitaxial growth includes providing a substrate and forming a plurality of modified points in an interior of the substrate in position corresponding to the modified region. A semiconductor device including the substrate and a method for manufacturing the semiconductor device are also disclosed.