18results about How to "Real-time update" patented technology

This invention discloses a method and system for labeling prompt words in a large-scale communication domain model based on knowledge graphs. Belonging to the fields of communication technology and artificial intelligence, it addresses the following technical problems: low efficiency in labeling specialized terms in communication domain prompt word annotation, low accuracy and efficiency of automatic recognition, limited prompt word dimensions, and lagging domain knowledge. The method includes: sequence labeling and entity extraction using a trained combined model to output entities; generating relation triples as candidate relations using a trained generator, and scoring and ranking the selected relation triples using a trained discriminator; semantic parsing of user input to extract key entities and intents; multi-hop reasoning from a dynamic knowledge graph to retrieve relevant entities and relations; eliminating illusory content using a trained GAN network; generating entity prompt words from three levels: basic, extended, and application dimensions; and introducing a triple quality verification mechanism.

This invention relates to a method and system for recalling recommended products in a second-hand e-commerce scenario. The method includes: acquiring real-time user behavior data; extracting the user's identity identifier and the identity identifier of the object product in the user's current behavior based on the real-time user behavior data; acquiring co-occurring products that form a co-occurring product pair with the object product from a data source; calculating the similarity between the object product and each co-occurring product; and sorting the multiple co-occurring products in descending order of similarity, selecting a predetermined number of co-occurring products at the top of the sorting as the recall products. This invention achieves real-time updates of the similarity of each product by storing the user's real-time behavior and promptly deleting expired user behavior, ensuring that the recommendation results are more relevant to the user's current or recent interests.

The application provides a rectal cancer VR preoperative planning three-dimensional modeling system with simulated physical properties, and belongs to the technical field of surgical modeling. The system comprises a medical image three-dimensional model reconstruction module, a VR interaction module, a model physical property assignment module, a surgical behavior analysis module and a simulation control module. The medical image three-dimensional model reconstruction module is used for constructing a three-dimensional anatomical model; the VR interaction module is used for constructing an interactive operation dataset; the model physical property assignment module is used for constructing a tissue mechanical state dataset; the surgical behavior analysis module is used for constructing a surgical operation action intensity coefficient, an operation continuity coefficient and a tissue stress change coefficient; and the simulation control module is used for dynamically presenting a tissue physical response effect under rectal cancer surgical operation in a virtual reality environment. The application makes the tissue physical response presented in the virtual reality environment consistent with the current surgical operation state, and improves the real-time performance and reliability of the simulation process.

This application relates to a construction safety monitoring device based on BIM and the Internet of Things (IoT). The device includes a data acquisition unit, a processing unit, a standardized physical interface, and an early warning unit. The data acquisition unit includes at least two different types of sensors. The processing unit communicates with the data acquisition unit via the standardized physical interface to receive site environmental data sent by the data acquisition unit and obtain risk analysis results. The processing unit also communicates with a BIM interaction interface to update the BIM model. The early warning unit communicates with the processing unit for risk warning. This device automatically monitors construction site safety without human intervention, solving the problems of low efficiency and reliability in construction site safety monitoring and reducing accident risks. The standardized physical interface supports flexible access to sensors and equipment, adapting to different construction site scenarios. Through the BIM interaction interface, dynamic IoT data is combined with the BIM model to achieve real-time updates of the BIM model.

The application provides a dynamic knowledge updating and privacy protection reasoning method based on retrieval enhancement generation, and relates to the technical field of artificial intelligence, which comprises the following steps: receiving a user request and constructing context data, updating and storing public and private knowledge bases; encoding the context data to obtain a context vector, and performing similarity retrieval in the public and private knowledge bases respectively to obtain public and private knowledge sets; performing privacy protection on the private knowledge set, mapping the private knowledge to semantic agent Token, calculating the weight coefficient of the semantic agent Token based on the correlation degree of the context vector and the private knowledge, and generating a semantic agent Token set; introducing reasoning constraints and templates, constructing a structured prompt and inputting a large language model, guiding the model to complete reasoning and generate a reasoning result, collecting feedback information and adaptively optimizing the model, thereby realizing dynamic updating of the knowledge base, ensuring the security of private data, and improving the accuracy and timeliness of large model reasoning.

The present application relates to a kind of city road network dynamic boundary control method based on event triggering, steps include: city road network is divided into multiple demand and density on homogeneity subzone, according to the relative position relationship of subzone, demand and MFD equation information, construct with the boundary control rate of subzone between as the control input of multiple subzone traffic system model;Real-time evaluation subzone state, when meeting event trigger condition, the outermost boundary of trigger subzone is defined as controlled boundary, wherein event trigger condition is obtained by reinforcement learning algorithm learning;Based on the determined controlled boundary, using model predictive control algorithm controls road network boundary, to maximize the number of trip as target calculation controlled boundary boundary control rate, obtain the optimal boundary control strategy.Compared with prior art, the present application can realize the real-time, dynamic adjustment of city road network boundary, effectively deal with various emergencies and traffic demand changes, improve the operation efficiency and response speed of road network.

The invention belongs to the technical field of SSD testing, and particularly relates to a method and system for compressing metadata to improve SSD testing efficiency, testing equipment and a storage medium. The method for compressing the metadata to improve the SSD test efficiency comprises the related steps of data structure definition, write-in frequency analysis, dynamic dictionary construction, incremental compression strategy selection, compression algorithm selection, compression data storage format, parallel processing implementation, real-time mechanism updating, rapid indexing and positioning and decompression strategy. By analyzing the analysis result of the write-in times of different blocks and elaborately designing the compression algorithm, efficient compression and rapid decompression are achieved according to the characteristics of the SSD metadata, the compression ratio is optimized, computing resource consumption is reduced, real-time updating of the SSD metadata is achieved, and the testing efficiency of the SSD is remarkably improved.

The application relates to the technical field of artificial intelligence and intelligent decision-making, and provides a business process optimization and intelligent decision-making method and device.The method comprises the following steps: determining multi-modal fusion features according to multi-modal business data and a business scenario; inputting the multi-modal fusion features and timestamp data into a target time sequence fusion transformer model to obtain a business demand prediction result output by the target time sequence fusion transformer model; determining a target decision threshold according to the business demand prediction result and a preset threshold adjustment strategy; and determining a target business process decision scheme according to the multi-modal fusion features, the business demand prediction result and the target decision threshold.The business process optimization and intelligent decision-making method and device provided by the application can realize business process optimization and high-efficiency, high-precision intelligent decision-making.

The present disclosure relates to the field of rail transit technology, and particularly relates to a railway train control system line data interlaced redundancy management method and system. A train simultaneously sends position and working condition information to ground data management equipment of a current station and a next adjacent station during operation; the current station and the adjacent station equipment calculate train front line data in combination with computer interlocking route information and send the train front line data to the train; the train simultaneously receives data sent by the two pieces of equipment, and generates a control curve based on message sequence number comparison and a preset data acquisition strategy to select the latest valid data. The present disclosure realizes real-time updating of line data and temporary speed limit information by constructing an interlaced redundancy data coverage network. The present disclosure ensures that the train can seamlessly switch to a backup data source in the case of single ground equipment failure or communication anomaly based on an intelligent data acquisition mechanism based on message sequence numbers, thereby ensuring safe and efficient operation of the train.

This invention discloses a method for analyzing hyperbolic dome skin data, belonging to the field of hyperbolic dome data analysis technology. The method includes the following steps: extracting data on glass configuration, four-sided dimensions, interior angles, wind pressure, elevation, and in-plane tilt angle through a parametric design platform, and performing cylindrical single-curved surface fitting optimization on the hyperbolic panel; parsing the curtain wall system drawing data and verifying it according to building appearance grade standards; performing structural safety calculations, cost and construction analysis based on integrated data; and finally generating a comprehensive report including a calculation report, a quotation list, and construction drawings. This invention achieves full-process automation from data extraction, surface optimization, structural verification to output, effectively improving the accuracy, efficiency, and reliability of hyperbolic dome design.

This invention discloses an online detection method and system for health hazard factors in drinking water based on pre-column derivatization, belonging to the field of water quality testing technology. The method includes: introducing a drinking water sample into a microfluidic chip-type derivatization reaction cell, where it reacts with a pH / temperature dual-response intelligent derivatization reagent to generate characteristic spectral derivatized products; acquiring spectral data using a micro fiber optic spectrometer, and calculating the derivatization efficiency in real time using a PID dynamic control model, automatically adjusting the reagent dosage and reaction conditions until the target is met; the target derivatized products are separated and purified twice by a two-dimensional chromatographic separation component and then transmitted to a dual internal standard correction machine learning model, where peak shape analysis, overlapping peak decomposition, dual internal standard correction, and quantitative regression calculations are performed to output the detection results and feed them back to the PID dynamic control model to update parameter thresholds. This invention improves the specificity, stability, and accuracy of the detection.

The application is suitable for the field of detection, and discloses a multi-motion target tracking counting method, device, equipment and storage medium.The method comprises the following steps: acquiring a current frame of an input image sequence in time sequence, performing foreground detection and morphological operation, then performing connected domain analysis to obtain multiple connected domains, and screening out connected domains with an area greater than a preset connected domain area threshold as current frame motion targets; when the size of the boundary box of the current frame motion target is greater than a preset boundary box splitting threshold, the current frame motion target is split into at least two current frame sub-targets; the current frame motion target and the current frame sub-targets that are not split are collectively referred to as current frame effective targets, the state of the current frame effective targets is updated through an association, creation and removal mechanism, and after the state updating of all the current frame effective targets is completed, the number of the current frame effective targets is counted.The method can split oversized targets, and ensures that each sub-target can be independently recognized and tracked.

The invention relates to the field of kitchen ware, in particular to cooking equipment and a control method thereof. A cooking space with a heat preservation function is defined in the cooking equipment, the cooking equipment is further provided with a dehumidification device and a water supplementing device, the dehumidification device is used for reducing the humidity of the cooking space, and the water supplementing device is used for increasing the water content of food in the cooking space. The control method comprises the steps that the heat preservation function is started; obtaining the water content of food in the cooking space; according to the water content, the operation states of the dehumidification device and the water supplementing device are adjusted, so that the water content of the food is kept within a set threshold value interval till the heat preservation stopping condition is met. Based on the method provided by the invention, the cooking equipment can bidirectionally adjust the water content of the food in the heat preservation process, so that the taste of the food is kept unchanged after heat preservation, and the problem that the taste of the food becomes poor due to excessive water absorption or insufficient water of the food caused by long-time heat preservation is avoided; and the use experience of the user is improved.

This invention relates to a joint estimation method for high-sensitivity parameters and State of Charge (SOC) of lithium batteries, belonging to the field of lithium battery energy storage technology. The invention obtains measured data through dynamic operating condition experiments of lithium batteries. Based on the structural characteristics of the equivalent circuit model and the actual identifiability of the model parameters, high-sensitivity parameters are selected. Then, a parameter estimator is designed to identify only the high-sensitivity parameters, while other battery model parameters are obtained using offline parameter identification methods, determining the mapping relationship between each parameter and SOC. Finally, a state estimator with an adaptive module is designed, combining the parameter estimator and the state estimator to establish an adaptive double-extended Kalman filter algorithm, achieving joint estimation of model parameters and SOC. This invention reduces computational costs by decreasing the number of identified parameters, enables real-time updates of high-sensitivity model parameters, and possesses high SOC estimation accuracy. It also exhibits strong robustness under interference from current and voltage measurement errors, making it highly practical.

The application discloses a kind of ultrasonic phased array encoding scanning three-dimensional real-time imaging method, comprising the following steps: step one: setting scanning parameter and imaging parameter;Let i=1;Step two: drive ultrasonic phased array array probe along the scanning direction moves, when encoder triggers data acquisition, the ultrasonic detection data of the i scanning position is collected, obtains the i S scanning imaging;Step three: the i S scanning imaging is converted into the i slice data, to update the i slice of volume data with the i slice data;Step four: based on the relative position relationship between observation point, volume data and projection plane, using ray casting algorithm processing volume data, obtains the real-time three-dimensional imaging based on ultrasonic phased array encoding scanning;Step five: judge whether need to continue to be measured object ultrasonic scanning: if yes, then execute step six;If not, then execute step seven;Step six: let i=i+1, step two is executed cyclically;Step seven: end ultrasonic scanning.

The application relates to the technical field of operation and inspection control or regulation systems, and discloses a collaborative operation and inspection control system based on AR virtual superimposed perception feedback and artificial inspection fusion, which comprises a feedback data sampling unit, a state evolution mapping unit, a logical fusion arbitration unit and an instruction execution driving unit. The logical fusion arbitration unit determines a feedback divergence characteristic value according to statistical distribution characteristics of a physical perception sequence, determines a confidence state and a fusion weight coefficient of a perception channel based on the feedback divergence characteristic value, selects a weighted fusion mapping relationship for the physical perception sequence and a predicted state feedback stream, and generates a collaborative control instruction. The application uses advanced feedback information generated by a dynamic mathematical model to offset the sampling lag of the perception channel, suppresses the step overshoot of an execution mechanism of a controlled object through a logical damping feature, solves the phase delay of closed-loop feedback in an unstructured dynamic disturbance scene, and improves the operation and inspection operation control precision and operation continuity.

The invention provides a multi-modal agricultural knowledge graph construction method based on a large language model. The method comprises the following steps: firstly, carrying out standardized preprocessing on multi-modal data such as texts, images and sensors in the agricultural field; constructing an initial agricultural knowledge ontology by adopting a top-down and bottom-up combined mixed mode, and identifying a new concept based on a large language model to realize dynamic updating of the ontology; fusing the text entity, the image feature vector and the sensor time sequence feature into a multi-modal triple and storing the multi-modal triple into an image database; and finally, analyzing a user query intention by using a large language model, and performing multi-hop path reasoning in combination with a graph neural network to generate a structured result. The problems that in the prior art, multi-modal fusion is difficult, knowledge updating lags behind, and semantic reasoning capacity is weak are solved, the integrity, timeliness and intelligent decision support capacity of the knowledge graph are improved, lightweight deployment and a federated learning mechanism can be combined, an edge computing scene can be adapted, and the data privacy protection requirement is met.

The application discloses an IPTV program recommendation method and system based on multi-source data, and mainly relates to the technical field of television program recommendation. The method comprises the following steps: collecting multi-source heterogeneous data, managing the multi-source heterogeneous data, and constructing a data base; based on a batch processing engine, extracting historical data from the data base and persistently storing the historical data into a feature vector database; accessing behavior logs reported by a set top box in real time, and writing real-time features extracted into a cache; based on full training data in the data base and feature vectors in the feature vector database and the cache, outputting a personalized program recommendation prediction result for a target user; and dynamically adjusting parameters of the recommendation model according to feedback behavior data of the target user for the recommended content, so as to realize continuous self-optimization of the recommendation effect. The application has the beneficial effect that it combines a deep learning recommendation algorithm, realizes real-time modeling of user interest, and accurately recommends programs.