Abstract: This application provides a signal transmission method, apparatus, and system. The method includes: generating an ultra-wideband signal, where the ultra-wideband signal includes a channel impulse response training sequence (CTS) field, and the CTS field is obtained by separately spreading at least one first preamble symbol based on a pseudo-random sequence; and sending the ultra-wideband signal, where the CTS field is used to determine a channel impulse response. This application can effectively improve ranging and positioning efficiency while implementing secure high-precision ranging and positioning.

Abstract: An initiating device randomly generates a sending time interval at which the initiating device sends ranging signal frames to a responding device such that an attacker cannot determine a rule of sending the ranging signal by the initiating device to the responding device and cannot send an interference signal at a same moment to perform interference and an attack, thereby enhancing information security of electronic devices during interactive communication.

Abstract: A method of training a model, a method of determining a word vector, a device, a medium, and a product are provided, which may be applied to fields of natural language processing, information processing, etc. The method includes: acquiring a first word vector set corresponding to a first word set; and generating a reduced-dimensional word vector for each word vector in the first word vector set based on a word embedding model, generating, for other word vector in the first word vector set, a first probability distribution in the first word vector set based on the reduced-dimensional word vector, and adjusting a parameter of the word embedding model so as to minimize a difference between the first probability distribution and a second probability distribution for the other word vector determined by a number of word vector in the first word vector set.

Abstract: The present disclosure relates to signal transmission methods, apparatuses, and systems. One example method includes sending a narrow band signal to a receive end, where the narrow band signal is used by the receive end to determine initial time-frequency synchronization information, and sending an ultra-wideband signal to the receive end, where the ultra-wideband signal includes a channel impulse response training sequence (CTS) field, the CTS field is used by the receive end to determine a channel impulse response, the CTS field includes at least one CTS symbol, and the CTS symbol includes at least one first preamble symbol or is generated by spreading at least one first preamble symbol.

Abstract: A battery pack housing for a battery pack comprising a plurality of battery cells is disclosed. The battery pack housing comprises a surround frame (20), the surround frame comprising a plurality of walls arranged to surround the battery cells (40), and a top panel (22) which is attached to the walls of the surround frame to form the top of the battery pack housing. The top panel (22) is attached to the surround frame (20) using an adhesive (50). The top panel (22) is removable from the surround frame (20) to allow access to internal components of the battery pack.

Abstract: The present disclosure provides a method and an apparatus of matching data, a device and a computer-readable storage medium, which are related to the field of artificial intelligence technology, and in particularly to the field of intelligent search and deep learning. The specific implementation solution includes: obtaining a first instance of a resume and a second instance of a job profile; determining, for a meta path, a resume feature data of the first instance and a profile feature data of the second instance, the meta path is a knowledge graph path from the resume to the job profile; and applying a classification model to the resume feature data of the first instance and the profile feature data of the second instance to determine a matching result between the first instance and the second instance.

Abstract: A computer-implemented method is provided. A dataset comprising a covariate matrix, a treatment vector, and an outcome vector is received. Using a trained causal model applied to the dataset, an inverse probability weighted (IPW) model estimation of treatment effect is generated. An inverse probability weighted estimation of groundtruth treatment effect is computed. A causal treatment error is calculated based on the inverse probability weighted model estimation of treatment effect and the inverse probability weighted estimation of groundtruth treatment effect.

Abstract: In certain examples, a causal inference model is trained on a re-balancing task in a self-supervised manner, using ‘unlabelled’ training data pertaining to multiple domains. Rather than approaching casual inference as a domain-specific task (e.g., designing one causal-inference approach for a particular manufacturing application, another for a particular aerospace application, another for a specific medical application etc.,) a general-purpose causal inference mechanism is learned from a large, diverse training set that contains many treatments dataset over many field/applications (e.g., combining manufacturing data, engineering data, medical data etc. in a single dataset used to train a single neural network). In other words, a cross-domain causal inference model is trained, which can then be applied to a dataset in any domain, including domains that were not explicitly encountered by the neural network during training.

Abstract: A method and device for optimizing parameters of a biometric recognition mode are provided, the method includes: repeating steps of selecting a first test data set SI from current decision space based on Latin Hypercube Sampling (LHS), obtaining a first set O1 of multi-objective values corresponding to the set S1 determined based on original evaluation and determining a first Pareto solution set of the set SI based on the set O1, wherein the decision space is composed of parameters of the biometric recognition model, selecting a second test data set S2 from the current decision space based on a Non-dominated Ranking Genetic Algorithm NSGA and obtaining a second set O2 of multi-objective values corresponding to the set S2 determined based on a trained agent model, determining a second Pareto solution set of the set S2 based on the set O2, and updating the current decision space based on the set O1, the set O2, the set S1 and the set S2 until a condition is met; and determining a final Pareto solution set based

Abstract: The present application discloses a projection apparatus, a collection apparatus, and a three-dimensional scanning system with the same. The projection apparatus includes: a light emission portion, configured to emit multiple rays of preset light, wherein the multiple rays of preset light correspond to multiple preset wavebands, and the multiple preset wavebands are different from each other; and a light transmission portion, disposed on a transmission path of the rays of preset light, wherein the rays of preset light is transmitted via a preset pattern on the light transmission portion to generate target light projected to a target object in the form of color-coded fringes, and the light transmission portion transmits the rays of preset light corresponding to at least two different preset wavebands.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing the execution of the operations of a neural network. One of the methods includes obtaining data representing a graph characterizing a plurality of operations of a neural network, wherein each node of the graph characterizes an operation of the neural network and each edge of the graph characterizes data dependency between the operations; processing the data representing the graph using a graph embedding neural network to generate an embedding of the graph; and processing the embedding of the graph using a policy neural network to generate a task output, wherein the task output comprises, for each of the plurality of operations of the neural network, a respective decision for a particular optimization task.

Abstract: Disclosed in the present disclosure is a method for processing remote sensing images by fusing elevation information.

Abstract: Disclosed are a method and a system for data uploading, which belongs to the technical field of blockchain. The method comprises: receiving a block upload request sent by a slave server of a target node; determining whether block data corresponding to the block upload request has been uploaded to a block data storage system; if the block data corresponding to the block upload request is not uploaded to the block data storage system, acquiring the block data if the block data corresponding to the block upload request is not uploaded to the block data storage system, and uploading the block data to a storage space of the block data storage system; and sending an uploading success instruction to the slave server if the uploading is successful, so as to instruct the slave server to delete the block data stored on a light-weight peer in the target node.

Abstract: Embodiments of the present disclosure relate to a method and system for processing intraoral scanning, an electronic device, and a medium. The method includes: obtaining a positioning mode of a scan post in response to a request for scanning an oral cavity including scan posts, scanning the oral cavity to obtain target scanning data, and performing processing based on the positioning mode of the scan post and the target scanning data to determine positioning information of the scan posts.

Abstract: A computer-implemented method comprising: tuning first, second and third set of parameters of respective neural networks by minimising a loss function, the loss function comprising a sum of: a measure of difference between a distribution of a first plurality of latent vectors and a distribution of a second plurality of latent vectors; and an error determined based on a set of computed vectors, a set of computed mask vectors and ground truth data for the set of data.

Abstract: Disclosed in the present disclosure is a method for processing remote sensing images by fusing elevation information.

Abstract: The present disclosure a rapid degradation and mineralization method of per- and polyhalogenated organic pollutants (PHOPs), including injecting organic wastewater containing the PHOPs into a reaction chamber with a cathodic/anodic electrode system, adding an electrolyte to the organic wastewater and stirring evenly; adding a peroxide I and a peroxide II to the organic wastewater, and turning on a DC stabilized power supply and conducting a reaction, and at the end of the reaction, completing purification of the PHOPs in the wastewater. According to the present disclosure, peroxymonosulfate (PMS) and H2O2 are combined in electrolysis to accelerate the PMS decomposition in solution and produce more reactive oxygen species such as, ·SO4?, OH, singlet oxygen (1O2), and a superoxide anion free radical (O2?), thereby achieving cooperative of multiple oxidative and reductive reactive oxygen species, and especially increasing the generation of ·SO4? significantly.

Abstract: The present disclosure discloses an electrochemical regeneration method of activated carbon, including the following steps of placing activated carbon saturated with an organic compound into an electrolysis system containing a regeneration solution to serve as a cathode of the electrolysis system, adding a peroxide I and a peroxide II to the regeneration solution, connecting to power and conducting a reaction, and after the reaction is completed, taking out and drying the activated carbon to obtain regenerated activated carbon, where the peroxide I is a persulfate. The present disclosure is easy to operate and requires no addition of a metal ion. Many technologies are used and cooperated with each other to produce oxidative and reductive active species synchronously, thereby achieving efficient degradation and mineralization of refractory organic pollutants.