361 results about "Metadata analysis" patented technology

The invention relates to the technical field of financial data processing, in particular to a multi-source heterogeneous fund data processing method and system, and the method comprises the steps: recording source information through building a data source registry, and marking a unique identifier for data; performing differential analysis on the fund data in different formats to generate standardized column type storage data; traversing column type storage data to extract statistical characteristics, performing field classification through metadata analysis and financial dictionary matching, analyzing business connotations of fields difficult to classify in combination with a localized large language model, and mapping the business connotations to a header fusion knowledge graph; generating a mapping rule from the source field to the enterprise-level data model by applying a rule engine template on the basis of field classification and semantic recognition results; converting the data structure according to the mapping rule and executing standardization processing; the quality is further optimized through data cleaning; and finally, the data are verified, standardized fund data supporting data traceability are output, and the strict requirements of financial supervision application are met.

The invention discloses a low-code platform based on a component library and a form engine, and relates to the field of data processing. The platform comprises a design system, an application system and a service system. The design system is provided with a form designer and a template manager, the form designer can configure a form component to generate a description file, and the template manager supports separate storage of a page template; the application system comprises a form analysis engine, a UI rendering engine and a reusable resource management component, the analysis engine analyzes configuration generation logic, the rendering engine loads a resource rendering page, and the reusable resource management component stores resources and generates configuration; the service system comprises a metadata analysis engine and an SQL assembler, the metadata analysis engine analyzes business rules to generate SQL and filtering strategies, and the SQL assembler generates operation statements adaptive to multiple data sources. Through the modular architecture design and the dynamic analysis mechanism, the problem that a low-code platform is insufficient in flexibility and usability is solved.

Systems and methods for translating natural language to SQL on a custom enterprise data warehouse powered by Generative AI. With an embodiment of the present invention, a natural language question may be converted to a meaningful and accurate database query, e.g., SQL query, relevant to tables existing in an enterprise data warehouse. An embodiment of the present invention is directed to a comprehensive approach of transforming a natural language query to a focused SQL query using domain specific data models across firmwide metadata systems and data systems. In response to a user query, an embodiment of the present invention performs metadata analysis, targeted data retrieval and then SQL generation. An embodiment of the present invention may apply data warehousing standards and guidelines followed in the enterprise and provide a plug-and-play type architecture and solution that is scalable to large warehousing and other systems.

The invention relates to an automatic protocol adaptation method for a real-time access system of multi-source equipment. The data acquisition layer receives original protocol data sent by equipment and transmits the original protocol data to the protocol adaptation layer. And the protocol metadata analysis module extracts, analyzes, compares and matches the data, and automatically identifies the protocol type of the equipment. The rule engine converts original protocol data into a system unified internal data format according to a conversion rule and then transmits the original protocol data to the data processing layer, and after cleaning, integration, analysis and other operations are carried out, the original protocol data are transmitted to the application interface layer to be called by an upper-layer application system. And when new protocol equipment is accessed, the hot plug function allows the system to dynamically load the new protocol adapter module in a state of not stopping running. According to the method, automatic adaptation of a new protocol is achieved through rapid deployment of the containerized micro-service architecture in combination with newly added protocol rules and metadata of the protocol management module, the whole process does not need to compile and publish the system again, and efficient and stable operation of the multi-source equipment real-time access system is guaranteed.

The present invention provides a data processing method for a heart rate monitoring system, and belongs to the technical field of data processing. The present invention effectively solves the problems that heart rate monitoring systems have low accuracy in acquiring raw heart rate data of patients, have difficulty in removing heart rate interference factors, and require precise heart rate value data and analysis results. The present invention is used in a heart rate monitoring system, and the heart rate monitoring system comprises: a power supply apparatus, an information acquisition apparatus, an information conditioning module, a data fusion unit, a data analysis module, an anomaly detection alarm module, a display unit, and a storage unit. The present invention comprises the following steps: S1, information acquisition; S2, information conditioning; S3, data fusion; and S4, data analysis. The present invention can ensure that the heart rate monitoring system can accurately and reliably monitor and interpret heart rate data during data processing, thereby providing more reliable support for clinical practice.

An analysis system connects to a set of data sources and perform natural language questions based on the data sources. The analysis system connects with the data sources and retrieves metadata describing data assets stored in each data source. The analysis system generates an execution plan for the natural language question. The analysis system finds data assets that match the received question based on the metadata. The analysis system ranks the data assets and presents the ranked data assets to users for allowing users to modify the execution plan. The analysis system may use execution plans of previously stored questions for executing new questions. The analysis system supports selective preprocessing of data to increase the data quality.

The invention discloses an intelligent control system and method for production and processing of a photovoltaic panel, and relates to the technical field of intelligent control. During operation of the system, key data involved in the production process of the photovoltaic panel is collected, a light-transmitting effect data set, a durability data set and an electrical performance data set are generated and preprocessed, and a multivariate data analysis algorithm is applied to obtain a data set; and after calculation, obtaining a quality index Zlzs of the agricultural photovoltaic panel, receiving an analysis result of the data processing module, and performing real-time quality monitoring on the photovoltaic panel subjected to production process optimization by adjusting a material ratio, production environment parameters and a process flow. A quality index Zlzs of an agricultural photovoltaic panel is compared with a preset first quality qualification threshold value M and a preset second quality qualification threshold value N, potential quality problems in production are identified, a quality evaluation strategy scheme is obtained, an evaluation result is fed back to a production process optimization module and a data processing module, and a closed-loop control system is formed. And continuous optimization and quality improvement are realized.

The invention relates to the technical field of power distribution network fault early warning systems and methods, in particular to an intelligent power distribution network fault early warning system and method based on the Internet of Things, and the system comprises a sensing unit, a data processing unit, a data analysis unit, a fault early warning unit, a monitoring management unit, and a personnel inspection subsystem unit. The sensing unit is used for installing a current sensor, a voltage sensor, a temperature sensor and a humidity sensor at key node positions of a transformer, a switch cabinet and a line of the power distribution network, the current sensor is used for monitoring the current in the line in real time, the voltage sensor is used for monitoring the voltage value, and the temperature sensor is used for monitoring the operating temperature of equipment; faults are analyzed and judged from multiple angles, misjudgment and missed judgment are reduced, whether fault hidden dangers exist or not is judged more accurately, the operation state of equipment is evaluated in real time through monitoring of the Internet of Things, the frequency of manual inspection is appropriately reduced, the labor cost is saved, and the resource utilization efficiency is improved.

The invention discloses a fishing light complementation scene unmanned aerial vehicle inspection system, and relates to the technical field of unmanned aerial vehicle inspection, the fishing light complementation scene unmanned aerial vehicle inspection system comprises a ground management and control platform and a monitoring device which communicate with each other through a network, and the ground management and control platform is used for regularly collecting and identifying fishing light complementation scene image information and environment data; the image information and the environment data are processed, analyzed and pre-warned, the monitoring device is used for comprehensively monitoring the image and the environment data of the fishing-light complementary scene, and the ground management and control platform comprises a region division unit, a data analysis unit, a processor, a memory and a display panel. The monitoring device comprises a ground monitoring station and unmanned aerial vehicle equipment. The system can reduce the human resource cost, can cover the front and back of a photovoltaic panel, the center and the edge of a culture area and other traditional blind areas through the mutual cooperation of ground station fixed monitoring and unmanned aerial vehicle maneuvering inspection, can cover a large-area fishing-light complementary scene, and can greatly reduce the manual inspection cost and the equipment maintenance cost for a long time.

The invention discloses an agricultural crop monitoring system and method based on multi-source remote sensing data, and relates to the technical field of agricultural crop production, and the system comprises a ground remote sensing platform which is used for regularly collecting crop growth data and carrying out the recognition and prediction operation of crop growth vigor, the ground remote sensing platform comprises a crop region division unit, a data analysis unit, a data management server, a memory and a display panel; the monitoring device is used for carrying out omnibearing monitoring on the growth condition of agricultural crops, the ground remote sensing platform and the monitoring device communicate with each other through a network, and the monitoring device comprises a ground monitoring station and unmanned aerial vehicle equipment. Compared with a traditional manual monitoring mode and a single remote sensing monitoring mode, human resource cost can be reduced to a certain extent, crop growth conditions can be more comprehensively known through the unmanned aerial vehicle, the ground monitoring station and the like, the monitoring range is increased, the monitoring precision is improved, and abnormal changes in the crop growth process are found in time.

This disclosure relates to approaches for managing generative artificial intelligence content. Some aspects relate to managing and enforcing licensing conditions for various actors in generative artificial intelligence, such as content creators, model owners, and platform providers. Some aspects relate to lineage tracing, in which an asset is analyzed to determine what other assets it was based on and / or to determine which other assets were generated based on a given asset. Lineage tracing can be based on one or more of metadata analysis, hash analysis (such as perception hash analysis), or vector similarity. In some implementations, a vector embedding model is used to generate vector embeddings of assets, and the vector embeddings are compared to identify similar assets.

The invention discloses a data leakage risk assessment system, and particularly relates to the field of Internet of Things privacy leakage, and the system comprises a preprocessing module, an acquisition module, and an integration module. The preprocessing module executes traceability analysis and integrity verification on the endpoint log by constructing a preprocessing list of hierarchical JSON and verification Hash of the endpoint log, and the preprocessing module is used for identifying integrity abnormity of privacy leakage data of the Internet of Things; and the acquisition module executes encryption identifier extraction and protocol type mapping of an endpoint log through segmented sampling and parallel protocol analysis of network traffic metadata, and the acquisition module is used for acquiring an abnormal traffic mode of privacy leakage of the Internet of Things. Through endpoint log tracing, flow metadata analysis and protocol behavior mapping, the privacy leakage risk of the Internet of Things is detected from endpoint interaction and a flow mode without depending on the content of a data packet, and the leakage detection capability under encrypted flow is relatively improved.

An analysis system connects to a set of data sources and perform natural language questions based on the data sources. The analysis system connects with the data sources and retrieves metadata describing data assets stored in each data source. The analysis system generates an execution plan for the natural language question. The analysis system finds data assets that match the received question based on the metadata. The analysis system ranks the data assets and presents the ranked data assets to users for allowing users to modify the execution plan. The analysis system may use execution plans of previously stored questions for executing new questions. The analysis system supports selective preprocessing of data to increase the data quality.

The invention relates to the technical field of energy storage and utilization, in particular to an intelligent planning configuration management system for a household energy storage system, which comprises a data acquisition and transmission unit, a data analysis and processing unit and a decision execution unit, the data acquisition and transmission unit acquires and transmits related data of a battery and cooling liquid through a sensor and a thermal imager, and the data analysis and processing unit preprocesses, fuses and screens the data by using a denoising algorithm based on quantum noise cancellation and a multi-physical field data fusion algorithm based on holographic entanglement. A thermal health factor is calculated to evaluate the thermal health state of the battery, meanwhile, model predictive control and a multi-stage early warning algorithm are used for optimizing parameters of a thermal management system and early warning thermal faults of the battery, and a decision execution unit controls a coolant pump and regulates the thermal state of the battery according to the optimized parameters, so that the problem of inaccurate data processing of an existing household energy storage system is effectively solved. The safety and stability of the system are improved, and the service life of the battery is prolonged.

A method for managing an LCS includes: sending a request to a microvisor kernel (MK) of a microvisor to provision an LCS on a first IHS; initiating provisioning of the LCS based on a configuration template; receiving a notification, from the MK, specifying that the LCS has been provisioned; after the notification has been received: obtaining first metadata associated with the first IHS and second metadata associated with a second IHS; analyzing the first metadata and second metadata to extract relevant data; inferring, based on the relevant data, that the first IHS has at least the required amount of hardware resources to execute a vBMC associated with the first IHS; sending, based on the inferring, a second request to an SCP of the first IHS to generate the vBMC on the first IHS; and receiving a second notification, from the SCP, specifying that the vBMC is generated on the SCP.

The invention relates to the technical field of data analysis, and discloses a dialogue-based intelligent form distribution and data analysis system, which comprises a dialogue receiving unit, a form generation unit, a dialogue state tracking unit, a data distribution unit, a data analysis unit, a feedback optimization unit, an authority management unit and a multi-mode interaction unit. The dialogue receiving unit extracts user intentions and key entities, the form generation unit dynamically generates form templates according to the user intentions and key entities, the data distribution unit directionally distributes data, the data analysis unit mines data values, the feedback optimization unit optimizes the system according to analysis results, the authority management unit guarantees data safety, and the multi-mode interaction unit expands interaction modes. According to the method, intelligent form processing and data analysis are realized, the user experience and the working efficiency are improved, the potential value of the data is mined, and the safety and reliability of the data are ensured.

The invention discloses a new energy motor control system based on abnormality diagnosis, and belongs to the field of new energy automobiles. The new energy motor control system based on anomaly diagnosis comprises a data acquisition unit, a data analysis unit, an anomaly early warning unit and a visualization unit. The problem that the abnormity cannot be detected in time at present is solved, the operation data is collected in real time and preprocessed, then the preprocessed operation data is analyzed through the machine learning technology, possible abnormal conditions are found, if the abnormity is found, early warning information is generated, and an early warning notice is sent to management personnel, so that the safety of the management personnel is improved. According to the method, the new energy motor can be conveniently and timely controlled by a manager, meanwhile, feedback of an early warning notification of the manager is monitored to ensure that the manager timely responds to the early warning notification, and early warning information and data are visually displayed, so that the manager can be helped to more intuitively understand the operation condition of the new energy motor, and the operation efficiency of the new energy motor is improved. Therefore, stable and efficient operation of the new energy motor is ensured.

Examples of file analytics systems are described that may obtain metadata data from a virtualized file server using a snapshot of the file virtualized file. The analytics system may mount a snapshot to retrieve metadata used in determining an overall size, structure, owner, permissions, and / or storage locations of parts of a file system managed by the virtualized file server. The analytics tool may communicate directly with each of file server virtual machines of the virtualized file server during the metadata collection process to retrieve the respective portions of the metadata. During the metadata collection process, the analytics system may add a checkpoint or marker (e.g., index) after every completed metadata transaction to indicate where it left off accessing the metadata snapshots. The checkpoint may allow the analytics system to return to the checkpoint to resume the process should the process be interrupted for some reason.

The invention provides an intelligent member portrait analysis system based on multi-modal data fusion, and relates to the technical field of intelligent analysis. Multi-modal data is collected and integrated through the arrangement of a multi-modal data collection unit, a data analysis and processing unit, a portrait model establishment unit, a recommendation algorithm unit and a user feedback unit; the recommendation unit adopts different recommendation algorithms for different life cycle states of new users, active users and silent users and different behavior data of members in different states through analysis and processing to construct a portrait model, generate static and dynamic portraits and accurately insight member features and states, and the recommendation unit adopts different recommendation algorithms for different life cycle states of the new users, the active users and the silent users. And pushing the corresponding recommended commodity service content, thereby realizing timely and accurate commodity pushing for members in different life cycle states, and improving the use experience of member users.

The invention relates to the technical field of data acquisition, in particular to a data acquisition system based on edge computing, which comprises a sensor module, an edge computing module and a cloud server module, the sensor module is composed of various types of sensors, and the edge computing module comprises a data preprocessing unit, a data analysis unit and a data caching unit. The data analysis unit analyzes the preprocessed data in real time based on a preset analysis model, data feature extraction and pattern recognition are carried out, and the data caching unit is used for temporarily storing the analyzed key data and analysis results. According to the data acquisition system based on edge computing, real-time preprocessing, feature extraction, mode recognition and other operations are performed on the acquired data at the edge computing node, a simple decision task can be quickly judged, and once the equipment temperature exceeds a preset threshold value, the data can be quickly acquired. The edge computing node can immediately perceive and notify the production control system to take cooling measures, so that delay caused by data transmission to the cloud for processing is avoided.

The invention provides a campus second-hand commodity credible transaction evaluation system based on a block chain, relates to the technical field of commodity transaction, and effectively prevents bogus transactions by generating a user credit score Yxf, dividing a credit grade, linking authority and a margin mechanism; an image tampering trace is detected by adopting a convolutional neural network, an image consistency matching score Tsv is calculated in combination with metadata analysis and a multi-modal matching mechanism, the credibility is judged in a grading manner, and the misjudgment risk is reduced; transaction data is solidified through block chain evidence storage, an arbitration evidence packet is constructed, responsibilities are automatically divided based on a preset rule, the alliance chain consensus mechanism is utilized to ensure that data cannot be tampered and can be traced, and the dispute solving efficiency and transparency are improved; the fairness and security in second-hand commodity transaction are effectively improved, and the core problems of weak recognition of bad user behaviors, inaccurate pricing due to image information distortion and fuzzy dispute processing in a traditional system are solved from the system structure.

The invention relates to the technical field of coal mining, in particular to a dry coal preparation control system based on data analysis, which comprises a real-time data acquisition module, a data analysis module, a self-adaptive control module and a feedback optimization module. The real-time data acquisition module acquires information such as granularity, density, images and moisture of coal particles through a granularity sensor, a density sensor, an image sensor and a humidity sensor, and transmits data to the central processing unit. And the data analysis module analyzes the collected data based on a random forest algorithm to generate a sorting precision prediction value. The self-adaptive control module dynamically adjusts key parameters of the coal dressing equipment according to the predicted value by utilizing a PID control algorithm, and the key parameters comprise the wind speed, the screen inclination angle, the material flow speed and the like. The system not only improves the coal dressing precision and stability, but also improves the self-adaptive capacity of the equipment through intelligent control and optimization, and the system is suitable for popularization and application. The method has remarkable economic benefits and wide application prospects.

The invention discloses a distributed crane safety monitoring and early warning device which comprises a crane main body used for hoisting materials, the crane main body comprises hardware equipment and a software system, and the hardware equipment is used for forming the crane main body and comprises a cart operation assembly, a trolley operation assembly, a main beam, a hoisting assembly and a sensor assembly. The software system comprises a data acquisition unit, a data transmission unit, a data analysis and processing unit, an early warning unit, a control unit, a man-machine interaction unit and a data storage and query unit. According to the invention, various types of sensors are reasonably arranged on each key component of the crane, and multi-source data acquisition and adaptive sampling frequency adjustment technologies are combined, so that the spatial motion state, the load state, the self-structure state and the working environment of the crane are comprehensively and accurately monitored, diversified early warning modes and graded early warning mechanisms are provided, and the safety and reliability of the crane are improved. And the pertinence and effectiveness of early warning are improved by combining context awareness and intelligent voice early warning.

The invention provides a metadata management method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring a plurality of first metadata; taking the plurality of first metadata as input of a metadata analysis engine of the large model, and obtaining a plurality of standardized first metadata output by the metadata analysis engine; taking the standardized first metadata as input of a semantic understanding engine of the large model, and obtaining semantic vectors of the first metadata; clustering the semantic vectors of the first metadata, and identifying second metadata from the multiple pieces of first metadata according to a clustering result; taking the second metadata as input of a thinking chain inference engine of the large model, and obtaining a repair strategy of the second metadata output by the thinking chain inference engine; and executing the repair strategy of the second metadata to repair the second metadata. According to the embodiment, the problem of low metadata management efficiency in related technologies is solved, and the metadata management efficiency is improved.

The invention provides a heating ventilation heat supply dynamic control system, and relates to the technical field of heat supply system control, the heating ventilation heat supply dynamic control system comprises an equipment connection layer and a cloud processing layer, the equipment connection layer comprises a data acquisition module, a data transmission module and an instruction execution module, and the cloud processing layer comprises a data receiving module, an intelligent database and an instruction sending module. The intelligent database comprises a data storage unit, a data analysis unit and an instruction generation unit, the load state of the heating and ventilation equipment is obtained through a time sequence analysis algorithm in the data analysis unit, and optimized operation parameters are obtained through a self-adaptive genetic algorithm according to the load state; the method is based on a global optimization strategy, utilizes an intelligent algorithm, reduces manual intervention and avoids unnecessary energy waste, so that the overall energy utilization efficiency of the system is improved, energy consumption can be effectively reduced by reducing the output power or operation time of equipment when the load is relatively low, and quick response can be realized when the load is relatively high, so that the energy utilization efficiency of the system is improved. And stable operation of the system is ensured.

The invention belongs to the technical field of chemical process monitoring, and particularly relates to a chemical process safety monitoring device which comprises a central processing unit, a data acquisition unit, a data analysis unit, a human-computer interface unit and a warning module, through real-time monitoring, automatic alarm and intelligent control, potential problems can be recognized before danger occurs, and the safety of the chemical process is improved. Therefore, accidents are avoided or reduced, personnel safety and equipment safety are guaranteed, and the system can provide quick response before, when and even after accidents, effectively reduce accident loss and handle emergency situations such as leakage or explosion in time.

The invention discloses a clinical decision-oriented medical data analysis system, and relates to the technical field of medical data analysis, the clinical decision-oriented medical data analysis system comprises a patient end, a medical diagnosis end and a medical decision-making system, the medical decision-making system comprises a data acquisition unit, a data analysis unit, a decision-making output unit and a decision-making optimization unit; according to the method, the medical data is acquired, the disease course prediction model is established according to the historical diagnosis and treatment data of the patient, the disease course prediction result is obtained in combination with the medical data, and the medical seeing ability evaluation coefficient of the patient is obtained through comprehensive calculation based on the personal economic data of the patient and the social income data of the patient. The method comprises the following steps: judging the doctor-seeing ability of a patient according to a preset doctor-seeing ability evaluation interval, outputting a target decision scheme which can be loaded by the patient according to the doctor-seeing ability level of the patient, and when the scheme adaptation degree reaches a preset scheme evaluation threshold value, marking the target decision scheme as an optimizable scheme. And controlling and outputting a target optimization scheme by simplifying the examination process and the drug dosage in the treatment process.

The invention discloses a microfluidic-EICP combined dynamic visual monitoring system and method for a heavy metal polluted soil remediation process, and relates to the technical field of soil monitoring. The microfluidic-EICP combined heavy metal polluted soil remediation process dynamic visual monitoring system comprises a microfluidic reaction module, a multi-mode sensing module, a dynamic imaging module and a data analysis module, and the microfluidic reaction module comprises a heavy metal pollution simulation unit and an in-situ reaction control unit. The multi-mode sensing module comprises a substrate layer, a chemical sensing layer and a data interface layer, the dynamic imaging module comprises an optical imaging unit and a spectral analysis unit, and the data analysis module is electrically connected with the communication module. According to the technical scheme provided by the invention, multi-physical field cooperative monitoring of a chemical field, a mechanical field and a permeation field in the prior art is realized, and the cross-scale correlation analysis capability of a micro crystal growth mechanism and a macroscopic soil body modification effect is improved.

The technology disclosed relates to an introspector that scans an organization's accounts on cloud storage services and detects resources on the cloud storage services configured to store the organization's data, and identifies the detected resources in a resource list. The technology disclosed further includes an inline proxy that controls manipulation of the detected resources based on the resource list.

The invention relates to the technical field of internet advertisement services, in particular to a media advertisement putting interaction method and system, and the system comprises an advertisement customization module which is used for outputting a personalized media advertisement according to user data and comprises a data collection unit which is used for collecting the user data; the putting module is connected with the advertisement customization module and comprises an advertisement matching unit used for matching the media advertisement with an advertisement position of a media platform; the data analysis module is connected with the delivery module and comprises a feedback collection unit which is used for collecting feedback suggestions and evaluations of the users on the advertisements so as to output feedback data; the control module is connected with the advertisement customization module, the delivery module and the data analysis module and used for determining the fragment size of the feedback data according to the packet loss probability of the user data, and the media advertisement delivery interaction accuracy is improved.