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: 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 microbial fermentation method for improving tobacco quality, comprising the following steps: (1) inoculating flue-cured tobacco as an inoculation source into a tobacco powder medium, and cultivating at 20-40° C. for 20-50 h; (2) inoculating microbial liquid in step (1) into a fresh tobacco powder medium, cultivating at 20-40° C. for 20-50 h, and circulating for 15-25 cycles to obtain stable flue-cured tobacco microbial flora; (3) inoculating the microbial flora obtained in step (2) into the fresh tobacco powder medium, and culturing at 20-40° C. for 20-50 h to obtain seed liquid of the microbial flora; (4) centrifuging the microbial liquid obtained in step (3) and collecting microbes; (5) washing the microbes collected in step (4); (6) resuspending the washed bacteria in step (5) to obtain a microbial suspension; and (7) spraying the microbial suspension in step (6) to the tobacco leaves for fermentation for 6-8 days.

Abstract: Implementations of the present specification provide a training method for a graph neural network, and relate to performing multiple rounds of iterative updating on a graph neural network based on a user relational graph, where any round of the multiple rounds includes: processing the user relational graph by using a current graph neural network, to obtain multiple classification prediction vectors corresponding to multiple user nodes in the user relational graph; allocating a corresponding pseudo classification label to a first quantity of unlabeled nodes in the multiple user nodes based on the multiple classification prediction vectors; determining, for each of the first quantity of unlabeled nodes, an information gain generated by training the current graph neural network by using the unlabeled node; and updating a model parameter in the current graph neural network according to a classification prediction vector and a real classification label that are corresponding to each labeled node in the multiple us

Abstract: A cylinder assembly and a compressor having the cylinder assembly are provided. The cylinder assembly has a cylinder body, a valve assembly, a cylinder cover, a muffler, and a pressing cap. The valve assembly is arranged in the cylinder body. A sealing ring is arranged between the cylinder cover and the valve assembly. The muffler and the cylinder cover are integrally formed. The pressing cap is connected to the cylinder body. The cylinder cover is located between the cylinder body and the pressing cap, such that the pressing cap fixes the cylinder cover on the cylinder body.

Abstract: A connecting structure, an exhaust silencer, a silencer and a compressor are provided. The connecting structure has a connecting housing and an exhaust pipe assembly. The connecting housing has a silencing chamber and a sealing portion. One end of the exhaust pipe assembly passes through the sealing portion and extends into the silencing chamber. Another end of the exhaust pipe assembly is arranged outside the connecting housing. Thus, the silencing chamber is in communication with an outside space of the connecting housing through the exhaust pipe assembly.

Abstract: A method and system for cooperative charging between an unmanned aerial vehicle and an unmanned surface vessel includes: using the unmanned aerial vehicle to capture an image of the unmanned surface vessel; analyzing the relative position of a capturing device and the velocity of the unmanned surface vessel; controlling the unmanned aerial vehicle to approach the capturing device, and making the unmanned aerial vehicle to hover at a certain height within the capture range; detecting whether the unmanned aerial vehicle is within the capture range and, if within the range, using the unmanned surface vessel to capture the unmanned aerial vehicle or using the unmanned aerial vehicle to re-capture an image of the unmanned surface vessel; using the capturing device to adjust the position of the unmanned aerial vehicle and performing wireless charging.

Abstract: A display substrate includes a rigid substrate, a flexible substrate, a pixel structure, and bonding terminals. The rigid substrate includes a portion corresponding to a display region of the display substrate. The flexible substrate is disposed on the rigid substrate, and includes a portion corresponding to the display region and a portion corresponding to a bonding region of the display substrate. The pixel structure is disposed in a region on the flexible substrate corresponding to the display region. The bonding terminals are disposed in a region one the flexible substrate corresponding to the bonding region. The portion of the flexible substrate corresponding to the bonding region is bendable.