409 results about "Computer technology" patented technology

This disclosure provides a service recommendation method, apparatus, electronic device, medium, and product, relating to the field of computer technology. The method includes: filtering available services based on customer needs to generate a candidate service list; for each candidate service in the candidate service list, constructing an input sequence of the candidate service based on the customer needs and the candidate service; inputting the input sequence of the candidate service into an analysis model to obtain the matching degree between the candidate service and the customer needs; and obtaining a service recommendation result based on the matching degree between all candidate services in the candidate service list and the customer needs. This method can accurately identify the complex interaction relationships between customer needs and services, improving recommendation accuracy.

This disclosure provides interleaved pipeline scheduling methods, apparatus, devices, and storage media, particularly relating to the computer technology field, and more particularly to the artificial intelligence technology field, including deep learning, neural networks, and parallel computing. [Solution] A specific solution includes obtaining micro-batch scheduling parameters based on the pipeline splitting dimension, interleave dimension, and cumulative count; determining the transmission interval of a micro-batch requiring cache scheduling based on the micro-batch scheduling parameters; and performing cache scheduling on the computation results of the micro-batch requiring delayed transmission based on the transmission interval and cache units. According to this disclosure, a cache unit, for example, a cache queue, can be created, the computation results of some computation units can be cached in the cache unit, and the computation results can be transmitted with a delay. This allows for delayed transmission of the computation results of some micro-batches, improving the applicability of interleaved pipeline scheduling.

This application discloses a dynamic asset access control method, apparatus, device, and medium based on an operation and maintenance audit system, relating to the field of computer technology. It includes: upon receiving an access request for a target asset from a client, generating a corresponding mirrored traffic copy based on the currently transmitted original traffic using a preset switch, and parsing the mirrored traffic copy using a preset operation and maintenance audit system to obtain the target asset information; comparing the target asset information with data in a preset asset registration database using the preset operation and maintenance audit system to obtain the corresponding asset registration status; if the asset registration status is "registered," issuing a blocking command to the preset switch based on a preset access control policy using the preset operation and maintenance audit system, so that the preset switch can intercept the access request based on the blocking command. This addresses the shortcomings of traditional static solutions in terms of real-time performance, security, and audit integrity.

This application discloses a drone cargo delivery method, apparatus, device, and storage medium based on identity verification, applicable to drones equipped with sensors and cameras, and relating to the field of computer technology. The method includes: sending a random receiving code corresponding to the recipient's receiving location to receiving software; capturing a flash image of the recipient using the camera, detecting ambient brightness based on sensors, and adaptively processing the brightness of the flash image based on the ambient brightness; determining the flash brightness components based on the processed image using a target smoothing method, statistically analyzing the flash brightness components of each candidate region in the processed image, determining the target on / off state sequence corresponding to the flash based on the obtained flash energy sequence, and if the target on / off state sequence matches a preset on / off rule in the random receiving code, it indicates successful identity verification of the recipient, completing the corresponding cargo delivery operation. This improves the efficiency and accuracy of drone cargo delivery.

This invention discloses a data processing method, apparatus, electronic device, and storage medium, relating to the field of computer technology. One specific embodiment of the method includes: receiving a data processing instruction; obtaining the corresponding sliding window for each stored data; calculating the access parameters for each stored data; responding to a reporting instruction for the access parameters; obtaining the corresponding data identifier; obtaining the remaining expiration time of the data identifier to determine the current remaining time of the data identifier; and updating the local window lock of the data identifier based on the current remaining time; responding to a successful update of the local window lock; reporting the access parameters associated with the data identifier to a caching system; and responding to a triggering of a popularity acquisition task; obtaining the access popularity of each stored data from a preset caching system. This embodiment can solve the problem that analyzing client access data through a server requires establishing an independent server, resulting in high operational complexity and resource consumption.

This disclosure provides a method, apparatus, and electronic device for road speed recommendation, relating to the field of computer technology, particularly artificial intelligence, large-scale models, natural language processing, deep learning, mapping, and lane-level navigation. The specific implementation involves: acquiring vehicle trajectory data on roads associated with a map road network; wherein each road includes at least one road segment, and the vehicle trajectory data includes speed values ​​corresponding to multiple trajectory points; for any given road segment, determining a target trajectory point matching the road segment from the multiple trajectory points; determining the target trajectory speed of the road segment based on the speed value corresponding to the target trajectory point; fusing the target trajectory speed and target speed limit of at least one road segment to obtain the recommended speed for each road segment; wherein the recommended speed is used to provide speed recommendations for vehicles.

This application discloses code generation methods, model training methods, and related products, applicable to computer technology and AI fields. In this application, the code generation device deploys at least one model or has the ability to invoke at least one model. The device can acquire code to be converted written in a first programming language, perform semantic mapping on the code to be converted to obtain an intermediate representation, and use at least one model and the intermediate representation to obtain target code using a second programming language. This application utilizes at least one model to convert code into another programming language, achieving lexical-level semantic mapping during conversion, ensuring semantic consistency between the generated code and the original language, and enabling efficient and accurate conversion of the code's programming language. This application also provides corresponding model training methods and other related products.

A memory space configuration method and apparatus, and a computing device cluster, relating to the field of computer technology. The method is applied to a computing cluster, the computing cluster comprises a plurality of computing nodes, and each computing node among the plurality of computing nodes separately provides a memory space. The method comprises: allocating a first memory space in a computing node to a service running on the computing node, wherein the first memory space is used for storing service data of the service; and creating a binding relationship between the first memory space and a second memory space, wherein the second memory space comprises a memory space in the computing node different from the first memory space or a memory space in a computing node different from the computing node among the plurality of computing nodes, and the second memory space is used for providing backup data of the service data. The solution can achieve data protection at lower cost.

This application discloses a training method, apparatus, device, and storage medium for a joint angle prediction model, relating to the field of computer technology. The method includes: acquiring training sample data, which includes skeletal parameters, sample wrist joint pose sequences, and arm angle labels for the sample wrist joint pose sequences; obtaining arm angle feature information based on the sample wrist joint pose sequences using a selective state-space network of the joint angle prediction model to be trained; obtaining elbow position prediction information based on the arm angle feature information and skeletal parameters using a differentiable kinematic layer of the joint angle prediction model to be trained; and iteratively updating and training the joint angle prediction model to be trained based on a preset objective function, the training sample data, the arm angle feature information, and the elbow position prediction information to obtain a trained joint angle prediction model.

This application discloses a real-time control method, device, equipment, and medium for micro-nano air flotation phosphorus removal based on a neural network model, relating to the field of computer technology. It includes: real-time acquisition of operational data through a preset sensor network, and preprocessing the operational data to obtain target data; generating a recommended PAC dosage value based on influent phosphorus concentration, water turbidity, and historical phosphorus removal rate using a first preset neural network model, and dynamically correcting the recommended PAC dosage value based on potential data using a second preset neural network model to obtain the target PAC dosage; optimizing the dissolved air pressure based on the target PAC dosage, influent phosphorus concentration, water turbidity, historical phosphorus removal rate, and post-coagulation parameters using a third preset neural network model to achieve real-time control of micro-nano air flotation phosphorus removal. This enables real-time, adaptive, and intelligent optimization and control of operating parameters during the micro-nano air flotation phosphorus removal process.

This application discloses a method, apparatus, device, and storage medium for motion redirection, relating to the field of computer technology. The method includes: acquiring a motion capture sequence to be processed, the motion capture sequence including an upper limb motion sequence and a lower limb motion sequence; obtaining human arm span information based on a preset parametric human model and the upper limb motion sequence; converting the upper limb motion sequence based on preset arm span parameters of a target robot and the human arm span information to obtain an upper limb motion sequence of the target robot; obtaining an upper limb joint angle sequence of the target robot using an inverse kinematics algorithm based on the upper limb motion sequence of the target robot; performing information extraction processing on the upper limb joint angle sequence of the target robot to obtain three-dimensional spatial pose information corresponding to the upper limb joint angle sequence of the target robot; and determining the motion data of the target robot to be redirected based on the upper limb joint angle sequence and the three-dimensional spatial pose information of the target robot.

This application discloses a method, apparatus, equipment, and medium for fusing atmospheric boundary layer wind speed data based on a hybrid-system wind-measuring lidar, relating to the field of computer technology. The method includes: simultaneously acquiring coherent wind measurement data and direct sounding wind data currently measured by the hybrid-system wind-measuring lidar during atmospheric boundary layer wind field observation; performing spatiotemporal registration and preprocessing on the coherent wind measurement data and direct sounding wind data; fusing atmospheric boundary layer wind speed data based on the preprocessed wind measurement data and a current preset fusion model to obtain the current fused target wind speed data; the preset fusion model is a model constructed based on a heterogeneous dual-branch deep neural network; and determining the target atmospheric boundary layer wind profile based on the hybrid-system wind-measuring lidar and the target wind speed data. This application can achieve high-precision wind profile fusion, improving the accuracy, precision, and environmental robustness of atmospheric boundary layer wind speed data fusion.

This application provides a method, apparatus, device, medium, and program product for detecting use case redundancy, relating to the field of computer technology, and is used to improve the accuracy of use case redundancy detection. The specific technical solution is as follows: An original set of use cases is obtained, and the use case information of multiple use cases included in the original set is normalized to obtain a normalized set of use cases, which includes the normalized use case information of multiple use cases; based on the normalized set of use cases and the system version information corresponding to each use case, a use case genealogy diagram is established among the multiple use cases, which is used to characterize the relationships between the multiple use cases; based on the normalized set of use cases and the use case genealogy diagram, the redundancy type between each use case and its corresponding candidate use cases is determined, where the candidate use cases corresponding to each use case are: use cases that are redundant with each of the multiple use cases. This application is applied to scenarios involving the detection of use case redundancy.

This application discloses an method for displaying an interface and apparatus, an electronic device, a computer-readable storage medium and a computer program product, and relates to the field of computer technologies. The method includes: displaying an event reward interface, and displaying, on the event reward interface, a reward identifier of at least one stage in an event, the event including at least two stages, and each stage including at least two sub-stages; and displaying a reward identifier of a sub-stage within a first target stage in response to a reward identifier of the first target stage being selected, the first target stage being any one of the at least two stages included in the event, and the reward identifier of the sub-stage being configured for representing a reward allowed to be collected after the sub-stage is completed.

This application discloses a method, apparatus, device, and medium for network security incident assessment, relating to the field of computer technology. It is applied to a network security incident assessment system. The system deploys a large language model within an analysis chain framework to perform progressive reasoning. The method includes: extracting target assessment features related to network security threats from multi-source heterogeneous data; determining at least one threat hypothesis scenario based on the target assessment features; assigning positive weights to supporting evidence for the scenario and negative weights to rebuttal evidence for the scenario; performing reasoning analysis on the evidence set to generate a target assessment report for the threat hypothesis scenario; the evidence set is obtained based on target evidence carrying the aforementioned weights. This application avoids interference from different contextual scenarios in the judgment; avoids the problem of lack of reasoning basis in the reasoning process; significantly reduces misjudgments and omissions; and solves the problem of insufficient understanding and adaptability of general large language models to network security expertise.

This invention relates to the fields of computer technology and data processing, specifically to a user grading and rights matching system for mini-programs based on machine learning. The system includes: an initialization module that acquires historical behavioral data, inputs it into a preset model for processing, outputs a baseline state vector and bounded polynomial function parameters, and distributes them to the client-side cache; a data acquisition module that collects micro-interaction behavior data in real-time on the client side to obtain continuous behavioral variables; a grading calculation module that performs integral calculations by combining the baseline state vector and continuous behavioral variables to calculate transient continuous grading; a rights matching module that identifies conversion hesitation characteristics, substitutes the transient continuous grading into a function constructed from the function parameters for local solution, and generates and allocates target rights denominations; and a budget control module that locks the denomination boundary based on the function's global maximum value attribute to ensure that it does not exceed the global budget limit. This invention significantly reduces matching latency, avoids the risk of budget over-issuance, and demonstrates strong system robustness.

This application relates to the field of computer technology, specifically to a signal enhancement method, apparatus, and electronic device. The method involves acquiring a sound signal; extracting features from the sound signal to obtain sound features; performing enhancement processing on the sound signal using multiple sound enhancement methods based on the sound features to obtain multiple sound enhancement results; and using a fusion network to determine the fit between the sound signal and each sound enhancement method based on the sound features and the multiple sound enhancement results, and then weighting and fusing the multiple sound enhancement results according to the fit between the sound signal and each sound enhancement method to obtain the target enhancement result of the sound signal. Through the method provided in this application, when facing sound signals in different sound scenarios, the weights of the multiple sound enhancement results in the target enhancement result can be adjusted by changing the fit between the sound signal and the multiple sound enhancement methods in different sound scenarios, thereby ensuring the sound enhancement effect in different sound scenarios.

This application discloses a particle trajectory reconstruction method, apparatus, device, and medium based on flow-sensing implicit neural representation, relating to the field of computer technology. The method includes: constructing a spatiotemporal position embedding network based on Eulerian flow field information of the flow field surrounding an aircraft, utilizing a multilayer perceptron and implicit neural representation model to capture the spatiotemporal distribution and motion patterns of particles in the flow field around the aircraft; constructing a multi-scale residual learning module using Taylor expansion to balance trajectory learning at different time scales; constructing an initial particle trajectory reconstruction model using the spatiotemporal position embedding network and the multi-scale residual learning module; training the initial particle trajectory reconstruction model using target constraints; generating a target motion trajectory using the obtained target particle trajectory reconstruction model and based on the position information and integration time of the target particle in the flow field; where the integration time is the length of the target particle's motion time in the flow field. This improves the efficiency of particle trajectory reconstruction in complex flow fields.

This application discloses a method and electronic device for predicting intraocular lens (IOL) selection and rotation implantation, relating to the field of computer technology. This application acquires the user's ocular biological measurement parameters and constructs an intraocular geometric constraint region. The IOL is abstracted as a rectangular geometries, generating a set of candidate size-axis positions. Each candidate option satisfies the geometric constraints of the patient's intraocular anatomy in terms of implantation position and rotation angle. Based on this, by combining the geometric fit indices of the candidate options with individualized ocular biological parameters, the postoperative arch height, the probability of abnormal arch height, and postoperative refractive results are predicted. After post-processing and calibration, outputs with confidence intervals or risk probabilities are provided. This eliminates reliance on experience or rough estimates for surgical planning, effectively reducing the risk of arch height deviation or postoperative refractive errors, providing the optimal IOL option, and achieving individualized, quantifiable, and predictable implantation planning.

This invention provides a maintenance scheduling method and system based on an operations research optimization model, relating to the field of computer technology. The method includes: acquiring multiple maintenance tasks and candidate time windows corresponding to each maintenance task; using an operations research optimization model, with the goal of minimizing the total loss associated with executing each maintenance task, determining a target time window from the multiple candidate time windows; the operations research optimization model is configured with preset constraints, and the total loss includes at least one of the following: a first loss related to power generation revenue, a second loss related to contractual agreements, a third loss related to maintenance delays, and a fourth loss related to resource usage costs; generating a maintenance scheduling result based on the target time window corresponding to each maintenance task. This implementation can reduce revenue losses caused by maintenance and reduce scheduling conflicts, improving the executability of the target time window.

This invention discloses a method for comfortable anesthesia and controlled-release analgesia for daytime thoracic surgery, belonging to the field of computer technology combining computer vision and medical device control. The method involves: acquiring a first image acquisition command to control the image acquisition unit to acquire a facial region image stream of the subject at a first acquisition frequency; performing a wrinkle feature extraction operation on the current facial frame to obtain a first wrinkle feature parameter set containing contour length values ​​and grayscale gradient values; comparing this parameter set with a preset benchmark wrinkle parameter set to generate a wrinkle change offset; determining infusion control parameters from a preset control strategy mapping table based on this offset, and generating an infusion control command to instruct the infusion unit to perform the corresponding infusion action. This invention achieves refined control of the anesthesia process by real-time quantitative analysis of facial wrinkle morphological changes and automatically generating and adjusting infusion control commands.

This application discloses a memory management method and electronic device, relating to the field of computer technology. The method includes configuring the memory of any controller in a target cluster based on its current memory management parameters, running preset test cases on the controller to obtain performance indicators under the current memory configuration, determining the fitness function value of the controller under the current memory configuration, and then determining the controller's historically optimal memory management parameters. If the current iteration count has not reached an iteration count threshold, the memory management parameters are updated based on the target update speed, and iteration continues based on the updated memory management parameters. If the current iteration count reaches the iteration count threshold, the controller is configured with appropriate memory based on its historically optimal memory management parameters. This achieves dynamic memory management of the controller, resulting in improved memory utilization.

The application discloses a kind of commodity representation generation model training method and the method and device of associated commodity identification, it is related to computer technology field.The specific embodiment of the method includes calling commodity representation generation model, to calculate the residual vector of sample commodity based on the semantic information of commodity in sample commodity set, and further determine the semantic representation of sample commodity.By calling commodity representation generation model, to generate the co-occurrence representation of sample commodity based on corresponding user behavior information, finally according to the semantic representation and co-occurrence representation obtained training commodity representation generation model.This embodiment can be combined with the semantic information of commodity to represent the information of commodity, and accurately feature representation is carried out to commodity in combination with the co-occurrence information of commodity, to generate accurate commodity representation data, provide data basis for subsequent identification operation.

The utility model provides a kind of backlight touchpad with different visual graphics, it is related to computer technology field, including glass cover plate, diffusion subassembly, multi-pattern light guide subassembly, reflection subassembly, circuit board subassembly, glass cover plate, diffusion subassembly, multi-pattern light guide subassembly, reflection subassembly, circuit board subassembly are sequentially laminated and adhered fixed connection, light-emitting area is equipped on circuit board subassembly, the light pattern formed by the light of the light-emitting area of multi-pattern light guide subassembly can, according to the different area of pressing pattern, different pressing effect is realized;The backlight touchpad with different visual graphics can prompt different pressing area with different light-emitting pattern, improve the use function of touchpad.

This application relates to the fields of artificial intelligence and computer technology, specifically providing a risk decision-making method and system for the entire lifecycle of power data. The method includes: acquiring multi-source heterogeneous log data from the entire lifecycle of a power information system; using an unsupervised feature extraction module based on a variational autoencoder to extract latent feature vectors and determine the VAE reconstruction error; performing spatiotemporal feature extraction on the latent feature vectors to obtain the temporal behavior probability from the time-series analysis stream and the spatial graph embedding distance from the spatial analysis stream; and constructing a dynamic decision-making module based on a Bayesian network, using the VAE reconstruction error, temporal behavior probability, and spatial graph embedding distance as multi-source evidence nodes for the dynamic decision-making module to calculate the posterior probability of risk events. This application, through the collaborative fusion of spatiotemporal features and causal probabilistic inference, can significantly improve the safety risk perception and dynamic control capabilities of power data throughout the entire process of acquisition, transmission, and processing.

This invention provides a method and apparatus for multi-core computing resource scheduling in neural networks, relating to the field of computer technology. The method includes: dividing all neural network layers of the neural network to be inferred into at least one segment; merging adjacent neural network layers within each segment based on cluster merging relationships to obtain at least one cluster corresponding to each segment; iteratively adjusting all cores in the Multi-Core Module (MCM) based on the latency of each cluster to obtain the target number of cores for each cluster under load balancing; determining the partitioning method for each neural network layer based on its depth within the neural network to be inferred; and scheduling computing resources corresponding to the MCM for the neural network to be inferred based on all segments, all clusters corresponding to each segment, the target number of cores for each cluster, and the partitioning method for each neural network layer. This invention can deploy balanced clusters onto the MCM, simplifying hardware resource allocation.

This application provides a method, apparatus, device, medium, and program product for generating training data, which may involve artificial intelligence technology and computer technology. The method includes: inputting a first document from a data source corresponding to a vertical domain text retrieval model into a first large language model to obtain a query statement corresponding to the first document; querying the query statement in the data source to retrieve N second documents; where N is an integer greater than 1; selecting M target second documents from the N second documents that constitute negative samples with the query statement; where M is a positive integer; and for each of the M target second documents, constructing a triplet training data with a partial order relation for a general text retrieval model using the query statement, the first document, and the target second document. This automatic generation method of training data can improve the efficiency and accuracy of training data generation compared to manual methods.

This application relates to the field of computer technology and discloses a data processing method, system, medium, and program product. In this method, the data processing system first allocates corresponding computing resources for a first task. Then, it determines the transmission time required for the task data of the first task to be transmitted to the data processing system. During the transmission of the task data of the first task, a second task is executed based on the computing nodes allocated to the first task; the execution time of the second task is less than the transmission time. Corresponding to the completion of the transmission of the task data of the first task and the completion of the execution of the second task, the first task is executed based on the computing nodes allocated to the first task. Thus, even if the transmission of the task data of the first task takes a significant amount of time, the computing nodes allocated to the first task can execute other tasks with shorter execution times during the transmission of the task data of the first task, thereby reducing the waste of computing resources and improving resource utilization.

The application discloses a kind of lithium battery charge-discharge intelligent early warning method and system, belong to computer technology field.The method includes: when battery charges and discharges, actively injects multiple-frequency ac disturbance signal;Response signal is collected and is parsed to obtain dynamic electrochemical impedance spectroscopy containing charge transfer impedance and low-frequency phase angle;Based on the preset multidimensional health impedance mapping table, the reference impedance and reference phase angle corresponding to the current temperature and state of charge are inquired;Impedance relative deviation and phase angle offset are calculated;At least based on the deviation and offset, the internal micro-short circuit of battery is identified and early warning operation is executed;Through multidimensional mapping table and dynamic threshold mechanism, effectively eliminate working condition and aging interference, with high sensitivity and low false alarm rate;And supplemented by hierarchical early warning, standing verification and multi-cell collaborative calibration, the safety and usability of battery system are significantly improved.