862 results about "Information integration" patented technology

A federated distributed computational system enables secure collaboration across multiple institutions for multi-species biological data analysis. The system consists of interconnected computational nodes managed by a central federation manager. Each node contains specialized components that work together to process multi-species biological data while preserving privacy. These components include a local computational engine that handles data processing, a physics-information integration subsystem that combines physical state calculations with information-theoretic optimization, a privacy preservation module that protects sensitive information, a knowledge integration component that manages biological data relationships, and a communication interface that enables secure information exchange between nodes. The federation manager coordinates all computational activities and manages resource allocations across the network while ensuring data privacy is maintained throughout the process. This architecture allows research institutions to collaboratively analyze complex, multi-species biological systems through integrated physics-based modeling and information-theoretic approaches while maintaining security and confidentiality.

The invention relates to the technical field of machine vision, and discloses a machine vision-oriented cross-modal image-text analysis method, which comprises the following steps of: partitioning an input image to generate an image block sequence; inputting the image block sequence into a visual converter for multi-scale feature extraction, and generating target visual features; encoding the input text to generate a target text feature; inputting the target visual features and the target text features into a deep reconstruction bottleneck network for compression alignment, and generating a cross-modal compression vector; and inputting the cross-modal compression vector into a large language model to generate cross-modal decoding information, so that cross-modal redundant information can be effectively filtered, compact shared semantic representation can be learned, the information integrity of the compression process is ensured through bidirectional reconstruction verification, cross-modal semantic alignment is realized, and the method has the advantages of high efficiency and high reliability. Omnibearing cross-modal content generation from the whole to details is achieved, and the requirements of different application scenes are met.

The invention discloses a multi-dimensional information integrated transformer health state monitoring method, which relates to the technical field of power systems, and comprises the following steps: deploying a multi-source sensor, collecting various signals of a transformer, and carrying out signal conditioning and analog-to-digital conversion on analog signals collected by the sensor; performing timestamp alignment on the received multi-source heterogeneous data, and eliminating data noise by adopting a filtering algorithm; key features which are sensitive to the health state of the transformer and complement each other are selected from the extracted feature values to form a health state evaluation index set; setting a sliding time window, obtaining historical data in the window, performing normalization processing on the data, calculating the information entropy and the variation coefficient of each index, and fusing the information entropy and the variation coefficient to obtain the dynamic weight of each index; obtaining a health state index of the transformer according to the normalized value and the dynamic weight; and displaying the health state index and the change trend thereof in real time, and setting an early warning threshold value and an alarm threshold value of the health state index.

The invention relates to the field of standard comparison analysis, in particular to a method for automatically identifying differences of domestic and overseas standard files. A method for automatically identifying differences of standard files at home and abroad comprises the following four steps of S1, standard file analysis and information extraction, S2, semantic understanding and information integration, S3, standard difference comparison, S4, compliance analysis and suggestion, and in combination with a rule engine and a natural language generation technology, evaluating difference influences and outputting adjustment suggestions. According to the method, comprehensive analysis of the standard file is realized through multi-modal integration and structured processing, and a knowledge base with cross-language and format is constructed; clause association reasoning is realized through deep semantic analysis and knowledge graph construction; according to the method, accurate difference recognition is achieved through hybrid embedding and a dynamic threshold strategy, the accuracy and efficiency of standard comparison are remarkably improved, the manual intervention cost is reduced, and an efficient solution is provided for standard system analysis in international trade and technical cooperation.

The invention belongs to the technical field of computers, and particularly relates to an information integration management method and system supporting real-time updating, and the method comprises the steps: accessing a heterogeneous data source through a distributed gateway, carrying out the adaptive analysis of a protocol, and standardizing a structure; adding a millisecond timestamp and a unique identifier, and generating a semantic data cluster through streaming engine sliding window association analysis; after multi-dimensional consistency verification is executed, writing and storing are carried out by adopting a double-buffering and snapshot isolation mechanism; and dynamically assembling the customized view according to the user role and the context and safely returning the customized view. The system correspondingly comprises a protocol analysis module, a time sequence marking module, a streaming association module, a semantic verification module, a double-buffer control module, an index updating module, a view assembling module and a secure transmission module. According to the invention, millisecond-level real-time convergence, conflict-free fusion and on-demand view output are realized, and the data access flexibility, the quality guarantee capability and the service adaptation flexibility are comprehensively improved.

The invention relates to the technical field of building informatization, and discloses a construction collaborative management method and system based on BIM and Internet of Things. The method comprises the steps of building a BIM model, collecting field real-time data, generating a dynamic construction state through association, performing collaborative analysis and forming a scheduling plan, and finally realizing closed-loop management and control through feedback of the Internet of Things. The system comprises a BIM model construction module, a field data acquisition module and a collaborative analysis and scheduling module which are in collaborative linkage to realize information integration, state perception and dynamic optimization control in the whole process of building construction. The method can effectively improve the precision and efficiency of the engineering construction process, enhances the intelligent management and control capability of the construction site, and has good engineering practicability and popularization value.

The invention relates to the technical field of construction management, in particular to a tunnel construction progress real-time tracking system which comprises an environment monitoring module, a progress acquisition module, an anomaly recognition module, a risk assessment module and a resource allocation module. According to the method, through identification of the time sequence and the change amplitude of the tunnel excavation face environment parameters, pre-screening of potential progress interference factors, enhancement of influence factor perception ability and dynamic comparison of environment data and process progress are achieved, the process disjunction phenomenon can be captured in time, and the aging control precision is improved; through linkage analysis of operation time and equipment operation records, association analysis of abnormal positioning, scheduling response and progress offset section resource data is facilitated, operation node-level dynamic evaluation is achieved, allocation imbalance and high-frequency mismatched resources are avoided, operation time sequences are adjusted preferentially, field bottlenecks are relieved, and operation efficiency is improved. And real-time closed-loop linkage between the construction progress and resource configuration is enhanced through information integration and correlation analysis.

The invention provides a hydro meteorology early warning method for an offshore oil and gas platform, and belongs to the technical field of offshore hydro meteorology. Extreme weather events are identified by adopting minimum probability abnormal event identification vectors to match abnormal characteristic parameters, and abnormal signal characteristic parameters are input into an ocean dynamics prediction model to calculate real-time sea condition parameters; calling a multi-temporal-spatial-scale early warning fusion matrix to combine with a wavelet decomposition technology and a recurrent neural network to realize multi-scale information integration, analyzing an environmental parameter change trend through a sea condition jump identification model and triggering an emergency response, dynamically adjusting system parameters according to a stability evaluation index vector, and optimizing prediction precision by adopting an early warning residual value compensation matrix. And finally, multi-level early warning information is generated and a real-time early warning notification is sent to an operator, so that the technical problem of insufficient early warning precision of an offshore oil and gas platform hydro meteorology early warning system in multi-spatio-temporal scale data fusion processing is solved.

The invention relates to the technical field of machine tool cutter wear monitoring, and particularly provides an integrated multi-dimensional data monitoring system and a monitoring method.The integrated multi-dimensional data monitoring system comprises a multi-dimensional data acquisition module which can acquire multi-dimensional data of the working state of a cutter in real time; the feature information layer and the intelligent analysis layer comprise a multi-source data fusion module, an abnormal state recognition module, a residual life prediction module and a self-adaptive learning module; the decision execution layer comprises an early warning feedback module, a parameter optimization suggestion module and an intervention control module; the knowledge base system comprises a case base module, a rule base module and a model base module, different physical quantities are collected through the multi-dimensional data collection module, full-dimensional sensing of the state of the cutter is achieved in combination with machining features, material information and environment data, multi-sensor collection, physical model construction, feature information integration and intelligent algorithm analysis are combined, and the machining accuracy of the cutter is improved. And comprehensive, real-time and accurate monitoring of various abnormal states of the machine tool cutter is realized.

The invention discloses a sports video commentary generation method and system based on a multi-modal large language model, and the method comprises the steps: obtaining a multi-modal data set which comprises a sports video, and an audio and a commentary text corresponding to the sports video; constructing a multi-modal large language model, encoding the sports video, the audio and the explanation text so as to project corresponding video frames, audio waveforms and metadata to a shared embedding space, and determining a multi-modal embedding vector; a multi-modal clustering memory unit is set, multi-modal embedded vectors are grouped, and feature alignment between modals is optimized through comparative learning and information entropy regularization; based on a retrieval enhanced context learning mechanism, a historical instance is retrieved through sparse regularization distance measurement to serve as reference input of a current input multi-mode embedded vector; and jointly inputting the current multi-modal embedded vector and the reference input into the multi-modal large language model to obtain a sports video commentary. According to the method and the device, the problems of insufficient multi-modal information integration and insufficient context utilization are solved.

The invention relates to the field of industrial automation, in particular to an industrial robot glass processing system based on large model intelligent decision, and relates to an industrial robot key technology based on multi-source information integration and intelligent decision. Glass cutting is optimized through multi-physics field monitoring, the edge defects are reduced by 70%, and the rejection rate is reduced by 50%. And the edge grinding of the special-shaped glass is assisted by three-dimensional reconstruction, and the precision deviation is controlled within 0.1 mm. And multi-modal data improves the coating uniformity, the thickness deviation is within 5 [mu] m, and the film layer shedding is reduced by 80%. Multi-robot cooperation is achieved through reinforcement learning, the machining efficiency is improved by 60%, and the cost is reduced by 40%. And a digital twinning optimization process is adopted, so that the equipment failure rate is reduced by 60%.

The invention discloses an AI workflow processing method and system for intelligent hardware, and the method comprises the steps: obtaining multi-person cooperation input information, including voice, text and image information, through an edge device; the multi-user cooperation input information is processed, workflow related data is generated, and the workflow related data comprises a multi-user cooperation input information integration result, a work priority processing result, workflow distribution processing information, flow and computing power distribution information, plug flow interruption emergency processing information, live broadcast effect data and live broadcast setting optimization information; sending the workflow related data to cloud service equipment; receiving target format instruction information sent by the cloud service equipment; and determining a target application program based on the target format instruction information, and sending the target format instruction information to the target application program for the target application program to process.

The invention provides a feature extraction method and system for a three-dimensional CAD model and electronic equipment, and the method comprises the steps: a data processing step: generating a corresponding geometric attribute adjacency graph, an extended adjacency matrix, a spatial position matrix and a surface-surface shortest path side chain matrix based on the data of the three-dimensional CAD model; and a feature extraction step: performing semantic segmentation and instance segmentation on the processing features of the three-dimensional CAD model through a processing feature recognition neural network based on the geometric attribute adjacency graph, the extended adjacency matrix, the spatial position matrix and the surface-surface shortest path side chain matrix so as to perform feature extraction. By means of the mode, the geometric attribute adjacency graph and the novel descriptor are generated after the three-dimensional CAD model is recoded, information of the three-dimensional CAD model is prevented from being lost, and information integrity during data conversion is guaranteed. Semantic segmentation and instance segmentation are carried out on a geometric attribute adjacency graph and a novel descriptor through a specific neural network model, and the accuracy of feature extraction is improved.

The invention provides a large model agent interactive question and answer task decision-making method and system, and relates to the technical field of natural language process.The method comprises the steps that 1, user input is received through multiple rounds of dialogues, key information is extracted to form an initial memory node set, meanwhile, fuzziness and information integrity of a query intention are analyzed, and an initial memory node set is obtained; generating an uncertainty evaluation result; and step 2, based on the uncertainty evaluation result, evaluating the timeliness and importance degree of each node, generating an enhanced memory node set, and constructing a dynamic memory structure according to a semantic and sequential relationship to form a structured memory network. According to the method, the understanding accuracy of the intelligent agent on multi-round dialogue contexts, the logic continuity of decision response and the continuous adaptability of task processing capacity are improved.

The invention relates to the technical field of multi-view clustering, in particular to a multi-view clustering method and device, and can solve the problem that the overall effect of an existing method in a large-scale clustering task is limited due to the fact that the existing method has problems in the aspects of calculation efficiency, robustness and multi-view information integration to a certain extent. The method comprises the following steps: dynamically learning an anchor matrix and a projection matrix for each view, and constructing a bipartite graph to generate a similarity matrix; calculating a graph Laplacian matrix based on the similarity matrix of each view, and extracting spectrum embedding; the spectrums of multiple views are embedded and stacked into a third-order tensor, and cross-view shared information is extracted by using a low-rank tensor constraint; multi-view atlas embedding is aligned through a spectrum rotation technology, and a discrete clustering indication matrix is directly output.

The invention relates to the technical field of natural language processing, in particular to an archive structured information extraction method and system based on a multi-modal large model and a medium, and the method comprises the following steps: S1, establishing a mapping table of fields to be extracted; s2, data annotation; s3, constructing a layout analysis model, an archive structured extraction model and an archive structured integration model; s4, screening key information pages based on the layout analysis model; s5, extracting single-page structured information based on an archive structured extraction model; and S6, based on the archive structured integration model, integrating single-page structured information results. Through application of the multi-modal large model, accurate layout analysis, strong structured extraction capability and efficient information integration are realized, automatic extraction and integration from archive image data to structured information are realized, manual intervention is reduced, and processing efficiency is improved.

The invention relates to the field of artificial intelligence, in particular to a long text segmentation information retrieval result coherence enhancement method, system and equipment based on a knowledge graph, and the method comprises the following steps: receiving a long text input by a user; segmenting the long text into a plurality of segments according to a preset length, and recording the original position and sequence of each segment; performing named entity recognition on each fragment, and extracting a key entity; querying related information in a knowledge graph according to the key entity, and obtaining attributes of the entity and a relationship between the attributes; integrating the related information obtained by query into the corresponding text fragment to form a context enhanced fragment; receiving a user query request; calculating a correlation score based on the context enhanced fragment and the user query, and retrieving a related text fragment by using a hybrid retrieval strategy; and selecting the related text fragment with the highest score to generate a final answer, and outputting the final answer to the user. Therefore, the information integrity and the context continuity in the retrieval process are ensured.

The invention discloses a laser vision fusion navigation positioning method, device and equipment and a storage medium, and the method comprises the steps: obtaining point cloud data and image data of a current region, and achieving calibration through data alignment; performing fusion conversion processing on the aligned data to generate a fusion map containing geometric structure and semantic information; according to the fusion map and a preset neural network model, identifying passable areas, obstacle categories and position information from the fusion map based on the preset neural network model; and fusing the multi-target identification results to generate a navigation positioning map so as to provide environment model support for a navigation system. According to the invention, through advantage complementation of laser and visual data, model training and multi-source information integration, multi-dimensional perception of the environment is realized, and the accuracy and reliability of navigation and positioning in a complex scene are improved.

The invention discloses an internet e-commerce live broadcast dynamic management system, and relates to the technical field of internet e-commerce, the system comprises an e-commerce platform, the e-commerce platform is in communication connection with an information integration analysis module, a knowledge graph construction module, a commodity quality monitoring module, a trust rating module and a quality guarantee module, and the modules are in electric signal connection; and the information integration and analysis module is used for collecting and integrating commodity information, merchant qualification information and user evaluation information of the live broadcasting room to obtain an e-commerce information sequence table. By combining the machine learning algorithm and the knowledge graph, the commodity quality condition is monitored in real time, the commodity quality supervision efficiency is effectively improved, potential quality problems can be quickly identified, early warning notifications are sent to merchants and consumers in time, the merchants are prompted to rectify and modify in time, the risk that unqualified commodities flow into the market is remarkably reduced, and the market competitiveness is improved. The rights and interests of the consumers are guaranteed, and the credibility of the consumers on the e-commerce live broadcast is enhanced.

The invention provides an intelligence information integration method and device based on a multi-agent task chain strategy large model, and the method comprises the steps: collecting a plurality of pieces of open-source dynamic science and technology intelligence information of a target information source, and employing a literature analysis agent, an abstract induction agent, a content generation agent, a sequencing agent and a report generation agent which are constructed through a large language model; key information extraction, semantic analysis and induction, content evaluation and updating, information sequencing and version change recording and report generation are performed respectively, and automatic aggregation and sequencing of intelligence information are realized. According to the method, the defects of generalization, objectivity, cross-document information processing, flexibility, robustness, illusion rate, extrapolation ability, small sample learning ability and the like in intelligence information integration in the prior art are effectively overcome, the efficiency and effect of intelligence work are improved, and the intellectual property is improved. The method is of great significance in enhancing the service quality benefit of dynamic intelligence information and supporting strategic decision and policy making.

The invention discloses a question answering method and device based on retrieval enhancement generation, a medium and equipment, and relates to the technical field of computers. According to the method, related candidate sub-graphs are matched in an existing structured knowledge graph according to the query problem of a user, and the candidate sub-graphs are further judged to be insufficient to deal with the query problem through logical reasoning; according to the method, sparse keyword vectors of query questions based on surface vocabularies and dense question vectors based on context deep dependency are further extracted; matching the query question with a sparse semantic vector of each text block of the unstructured text based on surface vocabularies and a dense semantic vector of each text block based on context deep dependency, which are acquired in advance, so as to determine the text block related to the query question from the unstructured text; the candidate sub-graphs are further converted into graph structures to supplement the candidate sub-graphs, answers corresponding to the query questions are generated based on the graph structures, and the performance of questions and answers in multi-hop reasoning and information integration retrieval recall is improved.

The invention relates to the technical field of product data management, in particular to a food package printing material batch traceable management method and system, and the method comprises the following steps: collecting the production time of each production batch, constructing time data which comprises year, month, day, hour, minute and second, and creating a time code based on the time data; the time code is combined with the data of the production batch. According to the method, the time data of each production batch, which is accurate to second, is collected, the unique time code is constructed, and the time code and the batch production data are closely combined, so that a traceable time stamp data packet is formed, accurate correspondence between production information and time is ensured, and more efficient information integration and storage management are realized. In the storage process, classification and indexing are carried out in combination with batch time marking data packets, a data retrieval mechanism capable of rapidly responding is established, the information positioning speed and accuracy are improved, and the efficiency and reliability of batch query and tracking are improved.

The invention provides a PDF document intelligent word segmentation method based on content structure perception, and belongs to the technical field of computer information.The PDF document intelligent word segmentation method comprises the steps that firstly, by fusing layout analysis and multi-tool analysis, multiple types of content such as title levels, ordinary tables, characters in pictures and tables in the pictures in a PDF are accurately recognized and extracted; secondly, providing a structure-perceived word segmentation strategy, and carrying out differentiation processing according to content types, namely, dividing semantic blocks by taking a title as a guide, taking a complete table as an independent semantic unit, and carrying out context association on a picture OCR (Optical Character Recognition) result; and finally outputting high-quality knowledge fragments rich in metadata such as levels and types. According to the method, the information integrity and semantic accuracy of the PDF document during construction of the large model knowledge base can be remarkably improved.

The invention relates to the technical field of machine vision detection, in particular to a surface defect detection method and system based on curved surface coding and multi-view fusion, and the method comprises the steps: constructing a curved surface coding illumination system, generating a coding light field, and projecting the coding light field to a target surface; synchronously acquiring reflection images of the coded light field through a multi-view imaging device, and obtaining a multi-dimensional view image data set; separating light components from the multi-dimensional view image data set, and extracting a defect feature set; performing multi-view information integration on the defect feature set to obtain comprehensive defect features; and performing defect judgment and parameter calculation on the target surface based on the comprehensive defect characteristics, and outputting a defect detection result. By adopting curved surface coding illumination and multi-view fusion, gradient information carried by a coding light field and multi-view imaging to supplement space details, accurate detection of surface and subsurface defects is realized, the adaptability to high-curvature and multi-reflection characteristic targets is improved, and the problem of insufficient detection precision of irregular reflective surface defects is solved.

The invention relates to a man-machine cooperation fabricated construction management and control system and method based on a BIM and a Unity model.The BIM is integrated into a man-machine cooperation construction workflow through an interactive closed-loop digital twin framework, the closed-loop digital twin framework comprises a model building module, a man-machine interaction module, a middle layer module and a data collection module, the model building module is used for building a BIM model for the prefabricated part; the man-machine interaction module realizes manual remote control through a graphical user interface, issues an instruction to the robot, intervenes and supervises the construction process, and transmits the instruction to the middle layer module through a programming language; the middle layer module is provided with a data processing module, a machine autonomous control module and a decision information integration module; and the data is transmitted to the BIM through the data processing module to update the BIM model so as to reflect the change between the design construction state and the actual construction state. The method has the advantages that the participation degree of the building robot in site construction work is improved, and a solution is provided for intelligent construction of the fabricated building.

The invention relates to the technical field of voice signal processing, and discloses a voice segmentation intelligent editing system based on deep learning. The system comprises a voice feature extraction module, a segmentation boundary detection module, a semantic content analysis module, an editing strategy generation module and a real-time quality evaluation module. The voice feature extraction module collects multi-dimensional voice features and timestamp information, and verifies feature integrity and timeliness; the segmentation boundary detection module identifies voice pause intervals and semantic turning nodes and divides segmentation units and boundary types; a semantic content analysis module extracts text content and emotion features of each segment, and analyzes semantic topic relevance and information density; an editing strategy generation module formulates a segmentation retention rule and a sequence adjustment scheme, and matches user preferences and scene demands; the real-time quality evaluation module monitors voice fluency and information integrity in the editing process and analyzes splicing errors and user feedback. According to the system, intelligent processing of the whole voice editing process is realized.

The invention relates to a multi-round compression super-long text summarization system and method based on a large language model, and belongs to the technical field of natural language processing. The system comprises a text partitioning module, a semantic map construction module, a multi-round compression controller, a hierarchical abstract generator and an abstract fusion optimization module, a global semantic structure is extracted through semantic partitioning and map construction, a compression strategy is dynamically planned in the multi-round compression process, and a local abstract is generated. And finally fusing, optimizing and outputting a consecutive and redundancy-removed summary text. According to the scheme, the context length limitation of a large language model is broken through, and the information integrity and the processing efficiency of the super-long text abstract are improved.

The invention provides an external plug-in system based on retrieval enhancement. The external plug-in system comprises an indexing module, a retrieval module and a generation module, the index module is used for performing cleaning, segmentation, organization, semantic coding and storage tasks of text data; the index module comprises a dynamic data management sub-module, a strategy decision case library management sub-module, a Chinese character recursive segmentation sub-module, a tree index structure construction sub-module and a vectorization storage sub-module; the retrieval module is used for completing semantic matching and sorting on the basis of the structured index; the retrieval module comprises a double-tower rough arrangement sub-module, a cross fine arrangement sub-module, a real-time update sensing sub-module and a cache management sub-module; the generation module is used for carrying out integration and semantic modeling on the high-quality intelligence information provided by the retrieval module; the generation module comprises an information integration and reasoning sub-module and a credibility evaluation and feedback sub-module; the method supports fact alignment, real-time updating, logic interpretability and output evaluability.

The invention discloses an intelligent health management and insurance service integration system and method, and belongs to the technical field of information integration systems. An intelligent health management and insurance service integrated system comprises a user side, an insurance company side, a hospital side and a third-party server side which are in communication connection with a server. The user side is provided with an information acquisition module, a health monitoring module, a health service module and an insurance module. According to the invention, the health management and the insurance service are creatively and deeply fused, a one-stop integrated service mode is created, and the situation that the health management and the insurance service are mutually independent and the user needs to respectively search and connect is changed; according to the invention, the user can obtain accurate insurance recommendation and convenient claim settlement service while enjoying the health management service, and the insurance company can better develop business by means of the health management data, so that win-win of the user, the insurance company, the medical institution and the like is realized, and a brand new service concept and mode change are brought to the field of health insurance service.

The invention relates to a clinical nursing shift change system and method, and relates to the technical field of data processing, and the system comprises a nurse terminal module which is used for inputting shift change information through a standardized template, carrying out the continuous visualization of shift change, and carrying out the butt joint with an electronic medical record system, so as to automatically capture the abnormal and real-time data of a patient; the patient end module is used for generating a two-dimensional code scanning interface for a patient and family members to check nursing propaganda and education, guidance and diagnosis and treatment routes, and feeding back an abnormal state through a voice or graphical interface; the doctor end module is used for synchronously displaying key medical parameters in shift change data, so that a doctor can mark a risk level and trigger a secondary confirmation process; the quality control management end module is used for generating a traceable responsibility definition coefficient; and the data analysis module is used for calculating a shift-change integrity score representing shift-change information integrity and a global shift-change quality index representing shift-change quality in real time. The system can improve the accuracy and efficiency of clinical nursing shift change.