Abstract: A registration method and an electronic device for visual navigation in dental implant surgery, comprising obtaining a three-dimensional model of a target tooth to be registered, an entity model of the target tooth and a second model of the target tooth, obtaining a position and attitude matrix of the three-dimensional model in a virtual coordinate system according to the coordinates of at least three points on a three-dimensional model of a substrate after the registration of the three-dimensional model in the virtual coordinate system, mounting the entity model of the target tooth onto a registration standard board, obtaining a position and attitude matrix of the entity model in the visual coordinate system according to three optical marks and the points on the entity model corresponding to the three points, and obtaining a correspondence between the virtual coordinate system and the visual coordinate system according to two position and attitude matrices.

Abstract: A computer-implemented method is provided for model training performed by a processing system. The method comprises determining a set of first weights based on a first matrix associated with a source model, determining a set of second weights based on the set of first weights, forming a second matrix associated with a target model based on the set of first weights and the set of second weights, initializing the target model based on the second matrix, and training the target model.

Abstract: Provided are a method and apparatus for processing a deterministic networking (DetNet) data packet. The method includes: performing, by a DetNet node, format encapsulation on a data packet of a DetNet application flow when the DetNet application flow passes through a multiprotocol label switching (MPLS) network, wherein an encapsulated data packet comprises a label indication and a flow identifier header; and forwarding the encapsulated data packet in the MPLS network.

Abstract: A method is provided for quantizing a neural network model performed by a processing system. The method comprises determining a scaling factor based on a distribution of weights associated with the neural network model, determining quantized weights based on the scaling factor and the weights associated with the distribution, determining a training loss of the neural network model based on the quantized weights during training of the neural network model, and determining an updated scaling factor for the neural network model based on a gradient of the training loss.

Abstract: Disclosed is a denture tray for visual marking and a manufacturing method thereof. The method comprises: establishing a three-dimensional model of a target dentition of a target patient; obtaining a three-dimensional model of a substrate of a denture tray based on the three-dimensional model of the target dentition; providing a through hole at a preset position on the three-dimensional model of the substrate of the denture tray; establishing a three-dimensional model of a fixed connection portion on an outer side surface of the three-dimensional model of the substrate of the denture tray to form a three-dimensional model of the denture tray, wherein the three-dimensional model of the fixed connection portion is integrally connected with the three-dimensional model of the substrate of the denture tray; and manufacturing the denture tray based on the three-dimensional model of the denture tray.

Abstract: The disclosure discloses a method and device for monitoring partial discharge. The monitoring method including: step a, connecting a monitoring circuit in parallel to both ends of a tested product, disposing a ground wire between the monitoring circuit and ground, disposing a first sensor in the monitoring circuit, and disposing a ground wire sensor on the ground wire; step b, applying an excitation signal to the tested product, acquiring a first signal through the first sensor and acquiring a ground wire signal through the ground wire sensor within a monitoring cycle; and step c, determining whether the tested product has partial discharge through the first signal and the ground wire signal. The disclosure can avoid the partial discharge monitoring device from wrongly determining an interference signal to be a partial discharge signal, enhance anti-interference capability of the partial discharge monitoring device, and improve monitoring accuracy.

Abstract: A liquid-solid axial moving bed reaction and regeneration apparatus and a solid acid alkylation process by using the liquid-solid axial moving bed reaction and regeneration apparatus.

Abstract: A data management system for collecting data of users from sensors at an event. An event-specific token corresponding to the event attended by the users is generated, where the event-specific token includes event-specific signatures about the users attending the event, and the signature of the event venue or facility. The public data is sent to public storage as an aggregation of the collected data and tagged with the event-specific token. The public data is statistically analyzed to track interactions and assess risks of the user's potential infection of a communicable disease based on anomalous activity detected at the event, or based on the notifications from the event attendees, which are matched and validated anonymously using the event-specific tokens. Based on a result of the statistical analysis, an advisory alert is sent to the users to warn them of a level of risk of harm based on attendance of the event.

Abstract: Provided is a substituted pyrimidine or pyridine amine derivative represented by formula (I), and a pharmaceutically acceptable salt, solvate, stereoisomer, prodrug, and pharmaceutical composition thereof, as well as medical application thereof. The derivative has significant adenosine A2A receptor and/or adenosine A2B receptor antagonistic activities.

Abstract: This disclosure relates to recommendations made to users based on learned behavior patterns. User behavior data is collected and grouped according labels. The grouped user behavior data is labeled and used to train a machine learning model based on features and tasks associated with the classification. User behavior is then predicted by applying the trained machine learning model to the collected user behavior data, and a task is recommended to the user.

Abstract: The present disclosure relates to a method and system for controlling a smart device. The method may include obtaining correlating information of the smart device. The correlating information may include at least one of smart device information or a communication status of the smart device. The method may include determining indication information of the smart device by processing the correlating information of the smart device according to a preset algorithm. The method may include performing designated operations related to the smart device based at least in part on the indication information.

Abstract: This invention provides a system and method for training and performing runtime 3D pose determination of an object using a plurality of camera assemblies in a 3D vision system. The cameras are arranged at different orientations with respect to a scene, so as to acquire contemporaneous images of an object, both at training and runtime. Each of the camera assemblies includes a non-perspective lens that acquires a respective non-perspective image for use in the process. The searched object features in one of the acquired non-perspective image can be used to define the expected location of object features in the second (or subsequent) non-perspective images based upon an affine transform, which is computed based upon at least a subset of the intrinsics and extrinsics of each camera. The locations of features in the second, and subsequent, non-perspective images can be refined by searching within the expected location of those images.

Abstract: A deep neural network based on analog FLASH computing array, includes a number of computing arrays, a number of subtractors, a number of activation circuit units and a number of integral-recognition circuit units. The computing array includes a number of computing units, a number of word lines, a plurality number of bit lines and a number of source lines. Each of the computing units includes a FLASH cell. The gate electrodes of the FLASH cells in the same column are connected to the same word line. The source electrodes of the FLASH cells in the same column are connected to the same source line, and the drain electrodes of the FLASH cells in the same row are connected to the same bit line. Each of the subtractors includes a positive terminal, a negative terminal and an output terminal.

Abstract: A node in a distributed network computes a hash of content for a service received in a data packet. The node verifies the data packet by comparing the hash of the content of a service received from a neighboring node to a hash of the content computed by the node. An amount of content of the service having a same identification is accumulated in a trusted execution environment (TEE) of the node, and a signature based on code stored in a TEE of the node is generated. The node then sends the data packet to the next neighboring node, where the service-related information includes the service ID, a hash of the service content and the signature. The service records with the accumulated amount of service content, accumulated hash values, and nodes' signatures are sent to the validation nodes to reach consensus for the service provided.

Abstract: An operating circuit and an operating method of a resistive random-access memory are provided, the operating circuit includes: at least one capacitance connected in series with the resistive random-access memory, so that the resistive random-access memory is grounded through the at least one capacitance. The operating method includes: connecting at least one capacitance in series with a resistive random-access memory, so that the resistive random-access memory is grounded through the capacitance; applying a forming pulse voltage or a set pulse voltage on the resistive random-access memory to achieve a forming operation or a set operation of the resistive random-access memory.

Abstract: The present disclosure relates to a method and system for controlling a smart device. The method may include obtaining correlating information of the smart device. The correlating information may include at least one of smart device information or a communication status of the smart device. The method may include determining indication information of the smart device by processing the correlating information of the smart device according to a preset algorithm. The method may include performing designated operations related to the smart device based at least in part on the indication information.

Abstract: A computer implemented method for self-learning of a control system. The method includes creating an initial knowledge base. The method learns first principles using the knowledge base. The method creates initial control commands derived from the knowledge base. The method generates constraints for the control commands. The method performs constrained reinforcement learning by executing the control commands with the constraints and observing feedback to improve the control commands. The method enriches the knowledge base based on the feedback.

Abstract: A computer-implemented method of answering questions comprises: receiving, by one or more processors, a query; based on the query, generating, by the one or more processors, a matrix; based on the matrix, modifying, by the one or more processors, a dynamic memory; based on the matrix, determining, by the one or more processors, a first response from the dynamic memory; based on the matrix, determining, by the one or more processors, a second response from a database; based on the first response and the second response, determining, by the one or more processors, a third response; and in response to the query, providing, by the one or more processors, the third response.

Abstract: Disclosed herein are systems and methods for machine vision. A machine vision system includes a motion rendering device, a first image sensor, and a second image sensor. The machine visions system includes a processor configured to run a computer program stored in memory that is configured to determine a first transformation that allows mapping between the first coordinate system associated with the motion rendering device and the second coordinate system associated with the first image sensor, and to determine a second transformation that allows mapping between the first coordinate system associated with the motion rendering device and the third coordinate system associated with the second image sensor.

Abstract: A computer implemented method for self-learning of a control system. The method includes creating an initial knowledge base. The method learns first principles using the knowledge base. The method creates initial control commands derived from the knowledge base. The method generates constraints for the control commands. The method performs constrained reinforcement learning by executing the control commands with the constraints and observing feedback to improve the control commands. The method enriches the knowledge base based on the feedback.