416 results about "Information mapping" patented technology

Systems, methods, and computer-readable for endpoint integration and mapping are disclosed. A system can include one or more processing circuits configured to identify endpoints and access information. The processing circuits can generate an object package corresponding to the endpoint by initiating the object package based on an identifier corresponding to an endpoint type of which the object package is structured and mapping the access information to an access scheme corresponding to formatted requests to access the endpoints for protection data. The processing circuits can perform an endpoint request by invoking the object package using at least one formatted request and receiving output data with a response to the endpoint request by a DCDSI system. The processing circuits can further update a distributed ledger or data source based on the output data.

The invention provides a multi-modal knowledge extraction method and system based on multi-agent collaborative optimization, and relates to the technical field of knowledge extraction, and the method comprises the steps: carrying out the multi-modal deconstruction of an original document to be extracted; constructing a multi-modal agent, respectively executing feature extraction and preliminary knowledge extraction, and outputting a single-modal multi-component system; based on a cross-modal knowledge graph, mapping information of different modals to a unified semantic node, and establishing cross-modal association and analyzing a logic chain through a graph neural network and a causal reasoning module; dynamically allocating resources according to the importance of map nodes, and screening structured knowledge; and through confidence analysis and node traceability evaluation, an intelligent agent cooperation mechanism is optimized, and increment correction is carried out on a result. According to the method and the device, the technical problem of low knowledge extraction accuracy and efficiency caused by insufficient multi-modal knowledge collaborative mining capability due to knowledge extraction of literatures by adopting a single agent in the prior art can be solved, and the knowledge extraction quality and efficiency are improved.

The invention relates to the technical field of underground drainage pipeline monitoring and hidden danger analysis, and provides an underground drainage pipeline hidden danger data analysis method based on big data, which comprises the following steps: acquiring data such as flow, water level, pressure and pipeline structure by using a multi-source sensor to form an original monitoring data set; preprocessing the data, extracting time domain, frequency domain and spatial topological features, and constructing a multi-dimensional feature vector; and inputting the feature vectors into a pre-trained hidden danger prediction model, and outputting hidden danger types and position coordinates. And constructing a spatio-temporal data analysis model based on the hidden danger position, generating a spatio-temporal correlation feature matrix, and performing dynamic risk assessment to obtain hidden danger development trend parameters. And the hidden danger information is mapped to a geographic information system, a three-dimensional visual analysis result is generated, and a graded early warning instruction is transmitted to a drainage pipe network operation and maintenance management system through a communication interface. The operation and maintenance management efficiency of the drainage pipeline can be improved, the hidden danger checking cost is reduced, and the safety and reliability of the drainage system are enhanced.

The invention relates to the technical field of industrial product defect detection, and discloses a defect detection method combining vision and X-ray detection technologies, which comprises the following steps of: synchronously acquiring vision image data and X-ray transmission data in a surface coverage area of a detection object, performing combined preprocessing to complete noise suppression, artifact elimination and time alignment, and then acquiring the X-ray transmission data; according to the method, surface texture features and internal structure features are extracted respectively, cross-dimensional information mapping is performed through a multi-modal association module to generate a fusion feature set, surface damage, internal holes and boundary discontinuous defects are identified, and finally, a hierarchical detection report is generated according to defect space distribution and severity and is updated continuously. According to the method, the advantages of vision and X-ray detection are integrated, cooperative detection of surface and internal defects is achieved, the comprehensiveness, accuracy and real-time performance of defect detection are improved through multi-modal data synchronous collection, feature fusion and dynamic report generation, and the method is suitable for part quality detection in the industrial manufacturing field.

The invention discloses a policy recommendation method and system based on a heterogeneous knowledge graph, and relates to the field of policy recommendation, and the method comprises the steps: obtaining an original policy text from a plurality of heterogeneous policy data sources, and extracting policy-related information; mapping the policy-related information into policy entity nodes; mapping the enterprise portrait data into enterprise entity nodes; defining and generating multiple types of edges between the policy entity nodes and the enterprise entity nodes based on a preset semantic relationship so as to construct a heterogeneous knowledge graph, constructing a graph neural network model, and executing embedding calculation on various nodes in the graph so as to obtain node representation vectors; and obtaining a matching degree, and outputting a recommended policy entry set according to the matching degree as policy recommendation information of the target enterprise. The method not only breaks through the problems of format dependence, rule stiffness and semantic shallow hierarchy of a traditional policy recommendation system, but also has relatively high universality, interpretability and actual deployment value.

The invention discloses a server actual hard disk physical slot position and hard disk information mapping method and device, and relates to the technical field of hard disk testing, and the method comprises the steps: marking a unique number through a hard disk recognition tool and a visual recognition case slot position under an operating system, highlighting a hard disk in combination with a lighting mechanism, and carrying out the recognition of the unique number through the slot position association after lighting. According to the method and the device, the actual hard disk SN code is established, the mapping relation between the actual hard disk SN code and the visual physical slot position is established, and the unique mapping between the actual hard disk position and the hard disk information is established through the mapping relation between the SN and the actual physical slot position, so that the problems of low efficiency of a hard disk testing technology, easiness in mistaken formatting, mistaken unloading and mistaken plugging after disk letter disorder, and high reliability are solved. According to the technical scheme, the technical problems that a storage path cannot be found in time, and the accuracy and efficiency of hard disk management are seriously affected are solved, and the technical effects that decoupling of the storage path and physical hardware is ensured, the influence of system restart or hardware change on services is reduced, the fault hard disk can be directly positioned through slot position identification, and the fault recovery time is shortened are achieved.

The invention provides a transformer substation operation and maintenance-based lock control terminal work log query method and system, and the method comprises the steps: collecting an original operation log stream generated by a transformer substation lock control terminal in a preset time period, serializing the original operation log stream to obtain a log data sequence, and then carrying out the context correlation analysis and recognition of an entity interaction relationship and behavior attribute description in a log text; a structured log metadata set is obtained after standardized integration; constructing a spatial topological index based on the physical layout and the electrical connection relationship of the substation equipment, mapping the equipment associated information in the spatial topological index to a corresponding node position of the spatial topological index, and generating a spatial enhanced log data set; receiving a natural language query request, generating a structured query expression, performing multi-dimensional retrieval matching on the spatial enhancement log data set, and outputting a preliminary query result set; and carrying out time sequence correlation analysis and operation influence evaluation on the log records to generate a query report. According to the invention, efficient and accurate query of the work log of the transformer substation lock control terminal can be realized.

Methods and corresponding systems and apparatuses for configuring user access to data stored in and / or accessed through an external computer system are described. Access permissions can be configured through defining a permission set relative to a proxy entity and assigning the permission set to one or more users. A proxy entity is a local representation of an external data entity. A proxy entity can be a virtual entity in that the proxy entity does not contain underlying data. A proxy entity can, however, include metadata describing its corresponding external data entity. A computer system maintaining a proxy entity can store mapping information linking the proxy entity to an external data entity. The mapping information and the permission set can be used to determine an access permission relative to the external data entity and to communicate this access permission to the external computer system so that access can be provided accordingly.

The invention relates to the technical field of data processing, in particular to an HTML (Hypertext Markup Language)-based webpage word cutting annotation generation method, system and equipment, and aims to solve the problems of low storage efficiency, poor dynamic webpage adaptability, lack of fault tolerance and insufficient cross-browser compatibility of an existing word cutting annotation method. The method comprises the steps of capturing a selected area; obtaining DOM node path data and text offset, and generating positioning data; recursively storing the path data to generate a unique fingerprint identifier; storing the fingerprint data as historical fingerprint data in a JSON format; performing matching and positioning based on the historical fingerprint data; and mapping information in the historical fingerprint data to an HTML page to realize bidirectional rendering. According to the method, the label name, the class name and the hierarchical relationship of the DOM node are recorded through the node path to construct the fingerprint identifier, and cross-platform data exchange is realized through the JSON structure, so that webpage labeling which is efficient, accurate, high in fault tolerance and adaptive to a dynamic page is realized.

The invention relates to a knowledge graph construction method and device, equipment and a storage medium. The knowledge graph construction method comprises the steps of obtaining a to-be-processed target text; extracting first text information from the target text according to preset first prompt information; wherein the first text information represents fact information of a plurality of entities in the target text; semantic recognition is conducted on the first text information, and the content type of the target text is determined; defining a plurality of nodes in a knowledge graph and an association relationship between at least two nodes according to the content type; and mapping the first text information into the knowledge graph to obtain a target knowledge graph of the target text. According to the method provided by the invention, the integrity and accuracy of information extraction are remarkably improved, meanwhile, the high-quality knowledge graph conforming to the text content type is constructed, and the precision and practicability of text analysis are improved.

The invention relates to the technical field of project progress management, and provides a multi-modal data driven project progress risk intelligent assessment method and system. Mapping the multi-modal engineering information into a third-order tensor, and generating a tensor slice of the third-order tensor as a space-time tensor based on a preset projection function; constructing a time-varying graph formed by engineering tasks and execution relations based on engineering information, extracting task features from the space-time tensor, generating edge weights based on the task features, adjusting node relations in the time-varying graph through the edge weights, and outputting a dynamic graph structure; based on the space-time tensor and the dynamic graph structure, generating a risk equation of the project progress in the space-time dimension, solving the risk equation through a differential equation, and outputting a risk item of the project progress; and generating a project progress risk assessment file according to the risk item and the actual progress data in the project information. Risk assessment errors are reduced, project progress risk assessment efficiency is improved, and project decision is supported to be converted from passive response to active intervention.

The invention relates to the technical field of data processing, in particular to a geographic information surveying and mapping data anomaly detection method and system based on data analysis, and the method comprises the steps: obtaining a deformation data sequence of a target monitoring point, calculating the edge degree of each piece of data, and screening edge points, selecting a point closest to the target edge point as a target point, screening an edge point of which the optimization degree meets a preset condition from the remaining edge points, connecting the edge point with the target point, taking a connection point as a new target point, repeating the connection process based on the new target point until a termination condition is met, and obtaining an edge; and taking the mean value of the deformation data of all the edge points in each edge as a clustering center of the corresponding edge, and clustering all the data according to the distance from each data to the clustering center, so as to monitor the deformation abnormity of the target monitoring point based on the abnormal degree of the obtained clustering cluster. According to the invention, accurate monitoring of abnormal deformation of the monitoring point can be realized.

The invention provides a power distribution control cabinet fault response method and device, and relates to the technical field of electrical automation control, and the key points of the technical scheme are that a weighted directed graph model representing the relation of internal components of a power distribution control cabinet is constructed in advance; mapping component fault information predicted by the digital twin system to attributes of corresponding nodes in the weighted directed graph model; identifying a fault path or a fault cluster satisfying a predetermined condition; for each identified fault path or fault cluster, calculating a composite risk index according to the prediction probability of the nodes included in the fault path or fault cluster, the weight of the connection edge and the severity of the influence on the system; and generating early warning information according to the composite risk index. According to the power distribution control cabinet fault response method and device provided by the invention, a potential fault propagation path or a fault aggregation area can be identified based on physical, electrical and influence relationships among components, and a composite risk formed by a plurality of potential fault combinations is quantified, so that a preventive maintenance decision is guided.

The invention relates to an industrial robot health state evaluation method based on multi-modal servo information mapping. The method comprises the following steps: obtaining the influence of a complex service condition on the performance of an industrial robot and a degradation mechanism; health perception features are extracted from multi-mode servo information collected in the operation process of the industrial robot; according to the collected health perception characteristics, a health perception model of the industrial robot under the complex working condition is established; an incremental learning model is established, a degradation model is obtained along with continuous addition, continuous learning and updating of new data, failure time distribution of the degradation model is predicted, decision support is provided for maintenance of industrial robot equipment, and a multi-modal servo information mapping model is constructed by deeply analyzing a performance degradation mechanism of an industrial robot under complex working conditions. And accurate sensing of the health state of the robot is realized. And a self-supervised contrast representation learning theory is utilized to solve the problem of fault sample deficiency, and the accuracy of health perception is improved. Based on an incremental learning theory of multi-modal servo information, an autonomous diagnosis model is established, and rapid diagnosis and performance degradation prediction of a new fault are realized.

An apparatus may include a receiver configured to receive a reference signal using a channel, a transmitter configured to transmit a representation relating to the channel, and a processing circuit configured to determine channel information based on the reference signal, generate, using a model, the representation based on the channel information, and transfer, using the receiver or the transmitter, model information to specify the model. The model information may include an identifier for the model. The model information may include structure information for the model. The model information may include information about a type of input for the model. The model information may include information about a format of input for the model. The model information may include mapping information for mapping channel information to an input of the model. The mapping information may include information for a first subband, and information for a second subband.

The invention relates to a component memory leak detection method and device, computer equipment and a storage medium. The method comprises the following steps: when a component creation event of a to-be-detected component is detected, generating a first heap snapshot corresponding to the component creation event of the to-be-detected component, and when a component destruction event of the to-be-detected component is detected, generating a second heap snapshot corresponding to the component destruction event of the to-be-detected component; analyzing the first heap snapshot and the second heap snapshot, and determining target structured data; component instance nodes are determined, and an information mapping table between node unique identifiers and node information of the component instance nodes is constructed; determining candidate memory leak components according to the information mapping table; and determining a target memory leak component from the candidate memory leak components according to the component-created document object model and the component-destroyed document object model of the candidate memory leak components. And the identification precision of the component memory leak scene is improved.

A user equipment maps a high priority hybrid automatic repeat request-acknowledgment / negative acknowledgment (HARQ-ACK / NACK) information to one or more resource elements (REs), and maps one or more of a low priority HARQ-ACK / NACK information, channel state information (CSI), or uplink-shared channel (UL-SCH) data to REs while rate matching around the mapped high priority HARQ-ACK / NACK REs. A network entity receives an uplink transmission, including high and low priority HARQ-ACK / NACK information, CSI, and UL-SCH data mapped to high and low priority HARQ-ACK / NACK REs, CSI REs, and UL-SCH REs, respectively. The low priority HARQ-ACK / NACK REs, the CSI REs, and the UL-SCH REs are rate matched around the high priority HARQ-ACK / N ACK REs. The network entity demaps and decodes the REs of the high and low priority HARQ-ACK / NACK, the CSI, and UL-SCH to obtain the high and low priority HARQ-ACK / NACK information, CSI, and UL-SCH data.

The invention belongs to the technical field of communication, and particularly relates to a high-robustness multi-channel frequency shift Chirp modulation signal generation method and system for a time-frequency doubly selective channel. The method comprises the following steps of: 1, calculating robust code digits based on statistical characteristics of time delay and Doppler frequency shift of an ionized layer channel; 2, based on the number of robust code bits in the step 1, setting an address code, and realizing RO-MFSCM signal mapping of binary information bits; 3, modulating and transmitting the RO-MFSCM signal based on the information mapping in the step 2, thereby realizing the transmitting process of the RO-MFSCM signal; step 4, based on the emission signal in the step 3 and the robust code digit in the step 1, the receiver carries out robust domain energy aggregation on the RO-MFSCM signal; and step 5, based on the multi-channel robust domain energy aggregation signal in the step 4, adopting a multi-channel parallel demodulation algorithm and de-mapping to realize the receiving process of the RO-MFSCM signal under the time-frequency doubly selective channel. The method aims at the transmission fading problem of the FSCM signal in the ionosphere time-frequency doubly selective channel.

The invention provides a server fault prediction method, device and equipment based on multiple modes, which are applied to the technical field of fault prediction, and the method comprises the following steps: collecting multi-mode data of a node server; the multi-modal data includes at least two of thermograms, system logs, GPU utilization, power consumption, temperature, fan speed and fan audio. And respectively extracting a modal feature corresponding to each modal from the multi-modal data. And fusing modal features of all modals in the multi-modal data, and predicting fault information of the node server. And mapping the fault information to the thermogram to obtain a fault risk map of the node server. The fault risk map is used for displaying the fault information in the thermogram in an overlapping manner. The problem that a traditional fault prediction method based on a single data source is difficult to discover hidden problems generated by a server, so that the fault of the server cannot be predicted in time can be solved.

The invention relates to the technical field of 3D development, and discloses a Three.js-based 3D scene low-code construction method and scene construction platform, and the method comprises the steps: a client obtains the operation information of a user, and sends the operation information to a server; the server side is used for mapping the operation information into the structured JSON Schema, updating the JSON Schema on the basis of the operation information, and carrying out persistent storage on the JSON Schema; and the server sends the JSON Schema corresponding to the preview request to the client, so that the client performs real-time rendering. According to the method provided by the embodiment of the invention, the graphical operation interface is provided, so that non-professionals can easily construct the 3D scene without mastering complex programming or graphical knowledge, and therefore, the user-friendly degree of the development process is improved, and the 3D scene construction difficulty is reduced.

The invention relates to the technical field of path planning, in particular to a pesticide spraying robot positioning method and system based on graph neural network multi-source fusion. Performing data preprocessing based on the acquired multi-source sensor information; graph node multi-modal data embedding is carried out on the preprocessed information based on perception information mapping; a multi-modal space-time diagram structure is built based on graph node multi-modal data embedding; performing graph feature propagation and fusion based on space-time attention weighting; and carrying out positioning calculation and path decision on the fused features based on spatial-temporal feature constraints. According to the method, a sensor observation graph structure is constructed, multi-source information such as GPS, IMU, vision, radar and the like is modeled in a node form, and nonlinear feature fusion is realized through graph convolution and an attention mechanism.

The invention relates to a text screen content image transmission method based on U-Net semantic segmentation, and belongs to the technical field of wireless communication and multimedia transmission. The method comprises the following steps: acquiring an original data set, and constructing an image semantic knowledge base according to the original data set; segmenting an input text type screen content image into a text region and a background region by adopting U-Net; respectively carrying out feature coding on the divided areas through an encoder, and mapping coded feature information to different subcarriers of OFDM through a channel attention module according to channel state information; power distribution of key features of OFDM is optimized through a space attention feature module according to the space features; the information is transmitted through OFDM, and the information is received at a receiving end and subjected to semantic decoding, so that an image is reconstructed, and a corresponding semantic task is executed. According to the method, the transmission accuracy and robustness of the text type screen content image in a complex channel environment can be remarkably improved.

The invention relates to the technical field of electromagnetic metasurfaces and bionic computing, and discloses a bionic information processing method and system based on an electromagnetic metasurface. The method comprises the following steps: S1, mapping DNA sequence information into a multi-dimensional coding state of the bionic metasurface information processing unit in an electromagnetic adjustable parameter space; s2, realizing co-evolution of the multi-dimensional coding state in space, frequency, phase and amplitude dimensions by dynamically regulating and controlling electromagnetic response parameters of the bionic metasurface information processing unit; and S3, using propagation and interference of electromagnetic waves in the diffraction neural network and a near-field coupling effect between the bionic metasurface information processing units to complete copying, logical operation and information read-write operation of the DNA sequence information. The functions of DNA coding, copying, logic calculation, information reading and writing and the like are uniformly mapped into the programmable electromagnetic metasurface platform, and cooperative processing of information in the aspects of space, electromagnetism and algorithm is achieved.

The medical field risk prediction system based on the NLP technology is composed of a medical data structuring processing part and a medical risk prediction part, and the data structuring processing part comprises the steps that S100, data cleaning and model pre-training are carried out, a Bert model is finely adjusted through collected medical text data, and a language model MedBert suitable for the medical field is obtained; s200: information extraction: extracting related entities, relationships and attribute information in the text through a pre-trained large language model, and structuring data; s300, standardization of the medical terms, mapping the extracted information to the standard medical terms through multi-strategy calling and negative sample training, and the risk prediction part comprises: S400, carrying out fine tuning pre-training on a TableBert model by using structured data, and extracting feature information of a patient from the data; and S500, through the risk prompt words and the extracted features, using a classifier to carry out probability prediction on corresponding risks, and solving the problems of low utilization rate and high application difficulty of unstructured data in the medical field.

The invention provides a crime category division method and system suitable for a large model, relates to a data processing technology, converts unstructured data into structured information through multi-modal evidence fusion and intelligent analysis, can quickly extract key elements of a case, and improves information processing efficiency. According to the scheme, the structured information is mapped to the virtual scene to generate video stream data, and key information of different subjects is visually displayed. By constructing structure tree data, key information of different subjects can be sorted and displayed hierarchically, and third-party data is introduced to calibrate event nodes. Compared with a traditional method, automatic processing of the case data can be achieved, and the data processing efficiency is improved.

Aiming at various tin planting devices in the production process of intelligent terminal electronic products, the invention provides a method for constructing a digital twinborn model of the tin planting device through a process flow description linked list and an internet of things information description linked list. According to the core idea of the invention core, a tin planting technological process and an internet-of-things information mapping chain table associated with the tin planting technological process are designed, the chain table is a descriptive and traceable model capable of forming time sequence association with the dynamic process of a solid production line tin planting device, and the descriptive performance of the model is suitable for constructing a twin model of any type of tin planting device; meanwhile, according to the time sequence of the technological process of the tin planting device, an internet-of-things interface mapping relation description model of the technological process description chain table and the internet-of-things information description chain table is established, and the model serves as an internet-of-things driving model to form a twin body of the tin planting device with a three-dimensional virtual animation model; and synchronous operation with the entity production line tin planting device is realized through a mapping synchronizer. The intelligent terminal electronic product production tin planting device twin system constructed through the method can be connected with a process control system of an entity production line tin planting device and an internet-of-things information detection system of the entity production line tin planting device for operation, and can also be independently operated off line after training; and analysis such as holographic state monitoring, operation optimization maintenance and the like is carried out through an internet-of-things information mapping model.

The invention discloses a document revision method, a document revision device and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: firstly, acquiring a reference document and a to-be-revised document in a revision mode; and analyzing the reference document, and extracting structured revision information corresponding to the reference revision operation trace. And analyzing the to-be-revised document to generate structured document information containing target content and target format information. And then, generating a cue word based on the semantic intention of the structured revision information, and inputting the cue word and the structured document information into the target model to obtain target revision information. And finally, mapping the target revision information to the to-be-revised document, and generating a target document with a target revision operation trace. According to the document revision method, the normalization and accuracy of the revision result can be ensured, the manual intervention cost is reduced, and format errors and semantic errors are reduced.

The invention discloses a scene intelligent extraction method based on L4-level automatic driving minibus road test data, and the method comprises the steps: collecting environment data and vehicle dynamic data, and carrying out the preprocessing, and obtaining time series data; constructing a DSFEM network, inputting time sequence data for training, and constructing a self-supervised loss function to update parameters of the DSFEM network to obtain time sequence features; clustering the time sequence features through a K-means clustering algorithm to obtain clustered scene features; constructing a manual annotation scene library, and calculating the similarity between the scene features to be stored and the behavior features of the existing scenes in the manual annotation scene library; an existing scene with the highest similarity is matched for the scene features, and manual annotation information corresponding to the existing scene is mapped into the scene features, so that scene automatic extraction and manual annotation scene library updating are realized; according to the method, the efficiency is remarkably improved in the aspect of scene generation, the reasonability and the coverage range of a scene library are ensured, and reliable support is provided for testing and evaluation of an automatic driving minibus.

The application relates to a dexterous hand self-adaptive grasping method, a dexterous hand control system and a storage medium, the dexterous hand self-adaptive grasping method comprising the following steps: acquiring multi-modal perception data; after processing point cloud data to generate a point cloud global feature vector corresponding to a grasping target, mapping tactile patch information to a dexterous hand workspace to generate a simulated tactile signal; processing the point cloud global feature vector and the simulated tactile signal by using a Glow-CVAE conditional generation model to generate a candidate grasping gesture set comprising joint posture and pose parameters; determining the stability corresponding to each candidate grasping gesture, selecting a target grasping gesture from the candidate grasping gesture set according to the stability, and grasping the grasping target by using the target grasping gesture. Through the application, the problem that the adaptability to special-shaped parts and flexible objects is limited and the grasping stability is not high in the related art is solved, and the beneficial effects of high adaptability and stability of grasping diversified articles in a complex scene are achieved.

The present disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. The present disclosure relates to a wireless communication system and, more particularly, to a method and a device capable of performing same, in which a terminal: transmits, to a base station, first capability information including a first indicator indicating that the terminal is capable of receiving and applying radio resource control (RRC) signaling in which multiple pieces of reporting configuration information may be mapped to a single measurement ID; receives, from the base station, a first RRC message including first configuration information in which multiple pieces of reporting configuration information are mapped to a single measurement ID; determines whether multiple reporting conditions corresponding to the multiple pieces of reporting configuration information are satisfied; and transmits a measurement report message to the base station if it is determined that the multiple reporting conditions are satisfied.