Abstract: This document describes techniques, systems, and methods for multi-scan sensor fusion for object tracking. A sensor-fusion system can obtain radar tracks and vision tracks generated for an environment of a vehicle. The sensor-fusion system maintains sets of hypotheses for associations between the vision tracks and the radar tracks based on multiple scans of radar data and vision data. The set of hypotheses include mass values for the associations. The sensor-fusion system determines a probability value for each hypothesis. Based on the probability value, matches between radar tracks and vision tracks are determined. The sensor-fusion system then outputs the matches to a semi-autonomous or autonomous driving system to control operation of the vehicle. In this way, the described techniques, systems, and methods can provide high-precision object tracking with quantifiable uncertainty.

Abstract: The present disclosure provides a point cloud encoding method and system, a point cloud decoding method and system, a point cloud encoder, and a point cloud decoder. A prediction mode of attribute information of a current point is determined through geometric information of a point in a point cloud, so that a determination process of the prediction mode is decoupled from a reconstruction process of the attribute information of the point in the point cloud, the two processes can be performed in parallel, and thus the efficiency of encoding and decoding is improved.

Abstract: Methods and systems are described that enable radar detection prioritization based on downstream feedback. As a vehicle is traveling in a travel corridor, radar detections are received by a processor and feedback related to a downstream function is received from another processor that is executing the downstream function. For the radar detections that are determined to be within the travel corridor, respective priorities are assigned based on locations of the radar detections and the feedback related to the downstream function. The radar detections with the assigned priorities are then stored in a detection buffer along with indications of their respective assigned priorities. In this way, the detection buffer may be optimized for the downstream function by filtering out certain detections and prioritizing others. Consequently, computational loads on the downstream function are reduced while ensuring that important detections are received by the downstream function early.

Abstract: A semiconductor wafer includes semiconductor dies and laser grooves formed in the scribe lines along the long edges of the semiconductor dies. A laser groove extends between the long edges of two adjacent semiconductor dies to encompass the corners of the two adjacent semiconductor dies. This prevents die cracking, for example during backgrind of the wafer. Moreover, the absence of laser grooves along the short edges of the semiconductor dies prevents die cracking, for example along short edges of dies overhanging empty space that are stressed during portions of the packaging process.

Abstract: An HFET includes a first and second semiconductor material. A first composite passivation layer includes a first insulation layer and a first passivation layer, and the first passivation layer is disposed between the first insulation layer and the second semiconductor material. The HFET includes a second passivation layer, where the first insulation layer is disposed between the first passivation layer and the second passivation layer. A gate dielectric is disposed between the second semiconductor material and the first passivation layer. A source electrode and a drain electrode are coupled to the second semiconductor material, and a gate electrode is disposed laterally between the source electrode and the drain electrode. A first gate field plate is disposed between the first passivation layer and the second passivation layer and electrically connected to the gate electrode, and a second gate field plate is disposed above first gate field plate.

Abstract: The invention provides a dental implant system with a surface gradient microporous structure and a preparation method thereof. The dental implant system includes a non-threaded micro-cone cylindrical dental implant and an abutment, wherein the dental implant includes a microporous layer with a bionic bone trabecular structure and a base with extremely high density and mechanical strength. The dental implant system of the invention has both the precision of the internal structure and the bionic characteristics of the surface structure, which effectively improves the long-term stability after implantation, reduces the complexity of the processing process of the dental implant system, and can realize personalized and batch production.

Abstract: A point cloud encoding method comprises: processing position information of a target point in a point cloud to obtain reconstruction information of the position information of the target point; obtaining an initial predicted value of attribute information of the target point according to the reconstruction information of the position information of the target point; filtering the initial predicted value of the attribute information of the target point using a Kalman filter algorithm to obtain a final predicted value of the attribute information of the target point; processing the attribute information of the target point in the point cloud to obtain a real value of the attribute information of the target point; obtaining a residual value of the attribute information of the target point according to the final predicted value and the real value of the attribute information of the target point; and encoding the residual value of the attribute information of the target point to obtain a bitstream.

Abstract: A point cloud decoding method comprises: parsing a bitstream of a point cloud to obtain reconstructed information of position information of a target point in the point cloud; obtaining predicted values of attribute information of the target point according to the reconstruction information of the position information of the target point; parsing the bitstream to obtain residual values of the attribute information of the target point; obtaining initial reconstructed values of the attribute information of the target point according to the predicted values and the residual values of the attribute information of the target point; filtering the initial reconstructed values of the attribute information of the target point by using a Kalman filtering algorithm, to obtain final reconstructed values of the attribute information of the target point; and obtaining a decoded point cloud according to the final reconstructed values of the attribute information of the target point.

Abstract: A point cloud encoding method includes the following. For one or more points in the current coding block, an optimal prediction mode is determined by using a RDO mechanism, where a distortion parameter D in the RDO mechanism is determined according to a reconstruction distortion, and a bitrate parameter R in the RDO mechanism is determined according to a bitrate. A prediction value of the one or more points is determined by predicting the one or more points using the optimal prediction mode. A residual of the one or more points is determined according to the prediction value of the one or more points. Encoding bits are determined by encoding according to the optimal prediction mode and the residual, and the encoding bits are signaled into a bitstream.

Abstract: A point cloud coding method, including: partitioning a point cloud, and determining a current coding block; determining a quantization parameter optimization enable identifier, a hierarchical level index, and a quantization parameter offset parameter of the current coding block; determining, according to the hierarchical level index and the quantization parameter offset parameter, a quantization step Qstep corresponding to a level of detail; and upon detecting that the quantization parameter optimization enable identifier is a first value, performing operations for one or more points included in the current coding block.

Abstract: A point cloud encoding method, including: obtaining attribute information about the attributes of a current point in a point cloud; processing the attribute information of the current point to obtain a residual value of the attribute information of the current point; using a target quantization manner, quantizing the residual value of the attribute information of the current point to obtain a quantized residual value of the attribute information of the current point; the target quantization manner comprises at least two of the following quantization manners: a first quantization manner, a second quantization manner, and a third quantization manner.

Abstract: Embodiments of this application are applicable to the field of artificial intelligence technologies, and provide a method and an apparatus for character selection based on character recognition, and a terminal device. The method includes: obtaining a connectionist temporal classification sequence corresponding to text content in an original picture; calculating character coordinates of each character in the connectionist temporal classification sequence; mapping the character coordinates of each character to the original picture, to obtain target coordinates of each character in the original picture; and generating a character selection control in the original picture based on the target coordinates. The character selection control is used to indicate a user to select a character in the original picture.

Abstract: The present disclosure provides a compound represented by formula (I), or a salt or a stereoisomer thereof. The compound is capable of effectively inhibiting germination of Clostridium difficile spores with a significant bacteriostatic activity. The compound has an excellent prospect for use in preparation of a drug for preventing and/or treating a C. difficile-caused infectious disease, recurrence of the C. difficile-caused infectious disease, or a complication of the C. difficile-caused infectious disease.

Abstract: A marine climate environment-bending load collaborative acceleration test method is provided, including conducting a static bending load loading test in an outdoor marine climate environment, conducting an alternate cycle of a dynamic bending load loading test in the outdoor marine climate environment and a test in the outdoor marine climate environment, and conducting an alternate cycle of the dynamic bending load loading test and the static bending load loading test in the outdoor marine climate environment. In the present disclosure, an acceleration rate of the marine climate environment-bending load collaborative acceleration test reaches over 8 times that of the test in the outdoor marine climate environment by taking the maximum bending force as an evaluation index, which may achieve a change from a static test to a static and dynamic combined test for examining and evaluating the environmental adaptability of the metal material.

Abstract: The present disclosure discloses an intelligent pet toilet. The intelligent pet toilet includes a main body; a door I is arranged on an outer wall of the main body; an inner wall of the door I is rotatably connected with a door II; a top outer wall of the main body is fixedly connected with a control panel; a cat litter storage chamber door is arranged on a top inner wall of the main body; a top of the inner wall of the main body is fixedly connected with a cat litter storage chamber; the inner wall of the main body is fixedly connected with a cat litter storage chamber motor; the inner wall of the main body is provided with a sensing device; the inner wall of the main body is fixedly connected with a pedal. The intelligent pet toilet is flushable.

Abstract: Disclosed are a pharmaceutical composition and method for relieving/eliminating morphine-induced analgesic tolerance. The pharmaceutical composition includes a therapeutically effective amount of a short peptide and morphine as active ingredients, and a pharmaceutically-acceptable carrier. The short peptide is a peptide consisting of an amino acid sequence shown in SEQ ID NO: 1 or a pharmaceutically-acceptable salt thereof. In the method, the short peptide and morphine are administered to a subject simultaneously; or the short peptide is injected to the subject followed by administration of the morphine; or a pharmaceutical composition including the short peptide and morphine is administered to the subject.

Abstract: A method for fluoroscopy energizes a radiation source to form a scout image on a detector and processes the scout image to determine and report a radiation field position with respect to a predetermined zone of the detector. The radiation source is energized for fluoroscopic imaging of a subject when the reported radiation field position is fully within the predetermined zone.

Abstract: A method is provided. The method includes receiving a set of data blocks to be stored in a storage system. The storage system includes a plurality of non-volatile memory modules. The method also includes generating a set of segments based on the set of data blocks. A respective segment comprising portions of one or more erase blocks. The method further includes writing the set of segments to the non-volatile memory modules based on orderings of the portions of the one or more erase blocks.

Abstract: A digital radiographic image of a subject is captured using a reduced exposure level of an x-ray source. One or more exposure control regions in the image is mapped and associated with a predetermined exposure level. A difference between the predetermined exposure level setting and the reduced exposure level is used to set a diagnostic exposure level perhaps about twice as high as the reduced exposure level to capture a diagnostic image of the subject.

Abstract: Embodiments of the present disclosure provide a method, device, and computer program product for error evaluation. A method for error evaluation comprises in accordance with a determination that an error occurs in a data protection system, obtaining context information related to an operation of the data protection system; determining, based on the context information and using a trained deep learning model, a type of the error in the data protection system from a plurality of predetermined types, the deep learning model being trained based on training context information and a label on a ground-truth type of an error associated with the training context information; and providing the determined type of the error in the data protection system. In this way, it is possible to achieve automatic classification of errors in the data protection system, thereby improving the efficiency in error classification and saving the operation costs.