196 results about "Data call" patented technology

The invention provides a dynamic data traceability method and system oriented to network security, and relates to the technical field of network security and data governance crossing, and the method comprises the steps: carrying out the real-time visual monitoring of a user interaction interface of a data transaction platform, and capturing the visual behavior information related to data calling; extracting feature parameters based on the visual behavior information to obtain a visual feature data set, and performing structured conversion on the visual feature data set to obtain a structured call log record containing visual behavior associated information; based on the structured call log record, extracting a time sequence, a frequency and a spatial distribution feature of a call behavior as basic indexes; a plurality of feature sampling states are dynamically selected in a monitoring time window, and a dynamic feature evaluation set is constructed based on the feature sampling states. According to the invention, the accuracy and controllability of network security protection in a data transaction scene can be improved.

The application relates to a composite robot multi-modal data encryption transmission method and system and a terminal, and relates to data transmission, which comprises the following steps: collecting information of a composite robot; classifying and encrypting the collected information through a preset encryption algorithm to obtain encrypted information; acquiring data calling information of the composite robot; determining whether the data calling information is consistent with preset reference calling information; if the data calling information is not consistent with the reference calling information, continuously acquiring the data calling information; if the data calling information is consistent with the reference calling information, encrypting the data calling information through the preset encryption algorithm to obtain encrypted calling information; and decrypting the encrypted information according to the encrypted calling information to obtain target collected information and outputting the target collected information to a preset calling platform. The application has the effect of improving the security of composite robot data transmission.

The invention discloses a subway tunnel full-section intelligent inspection robot system. The system comprises a mobile platform; a disease detection module; the data processing unit adopts an embedded industrial mainboard, is internally provided with a filtering algorithm and a ResNet50 deep learning model, processes the image and the point cloud in real time, automatically identifies the type, the position and the size of the disease and generates a three-level report; a main channel of the communication module is a double 5G industrial module, supports real-time uploading of a disease result, automatically switches a local cache when 5G is interrupted and supplementarily transmits the disease result afterwards, and is provided with a Bluetooth unit for on-site short-distance data calling; the power supply module adopts two groups of 12V / 100Ah lithium iron phosphate batteries which are connected in parallel, the endurance is greater than or equal to 4 hours, a brake energy recovery device is integrated, the battery is charged back during downhill or deceleration, the endurance is prolonged by about 15%, and one-hour fast charging is supported; and an auxiliary function module. According to the method, the consistency and reliability of detection data are remarkably improved, and a stable basis is provided for subsequent high-precision disease recognition.

The invention provides a rainstorm flood disaster chain monitoring field knowledge graph construction method, and relates to the technical field of knowledge graph construction, and the method comprises the steps: carrying out the preprocessing of original multi-source disaster data, and obtaining various types of quality-controlled data; calling a disaster field fine-tuning large model and an ontology inference engine based on the preliminary corpus and the multi-class quality-controlled data to generate a core ontology and a sub-document set, screening the sub-document set to construct a document association graph, and calling a mapping model to match a structured data field and a core ontology attribute; performing triple extraction according to the sub-document set and the constructed three-level cue word template; ontology instance attributes are vectorized and clustered, a three-layer collaborative system and an atlas core structure are generated through domain conflict repair and pruning density adjustment, a data calling disaster domain fine-tuning large model is obtained based on a processing process to complement an instance implicit relationship of the atlas core structure, and a target knowledge atlas is constructed. According to the invention, construction of the knowledge graph in the disaster field is realized.

The invention discloses an intelligent data calling method based on an MCP protocol, and the method comprises the steps: carrying out the intention recognition and key entity extraction in response to a natural language request of a user, and obtaining a plurality of user intentions and at least one key entity; judging based on the confidence coefficient of the key entity, and screening the user intentions according to the confidence coefficient of the user intentions to obtain an execution sequence containing a plurality of subtasks; and determining at least one target data source tool from a plurality of data source tools packaged based on the MCP protocol according to the description of the subtasks one by one so as to perform data query based on the key entity, obtain a query result and generate a final response. According to the method, the system decision reliability can be improved, the tool calling intelligence is enhanced, the process automation is realized, and the two major problems of low task planning quality and inaccurate tool calling are solved.

The invention provides a data sharing method and system. The intelligent level and compliance of data management can be improved. The data sharing method comprises the steps of performing classification based on structured data and unstructured data of to-be-shared data to obtain a data label and a data type; based on the data label and the data type, establishing a data asset directory of the to-be-shared data; obtaining a data calling application and a department sending the data calling application; based on the data asset directory, the data calling application, the information of the department and a preset rule, determining a data calling permission of the department; when the data calling permission of the department shows that the department allows calling, performing desensitization processing on the data based on the preset rule to obtain desensitized data; and sending the desensitized data to the department sending the data calling application.

The invention discloses a call request processing method and system, a storage medium and electronic equipment. The method is applied to a core network control node, and comprises the following steps: in response to a call request initiated by a calling party, obtaining call data of a call initiated by the calling party, the call data at least comprising a calling party number and a called party number; when the number of the called party is located in a preset first number list, adopting a plurality of call request evaluation models to predict the call request of the calling party to obtain a plurality of abnormal request probabilities; performing weighted fusion calculation on the plurality of abnormal request probabilities to obtain a target abnormal request probability; determining whether the call request is abnormal according to the target abnormal request probability and a preset probability threshold; and under the condition that the call request is abnormal, refusing to establish the call connection between the calling party number and the called party number. Therefore, according to the scheme provided by the embodiment of the invention, the processing precision of the call request is improved.

The invention relates to the technical field of intelligent voice data processing, and discloses an intelligent voice interface data calling method. The method comprises the following steps: receiving a voice instruction stream input by a user, and converting the voice instruction stream into a structured semantic unit set through a multi-level semantic analysis engine; and dynamically layering the instruction intention according to the semantic association degree in the structured semantic unit set to generate an intention sequence with priority marks. And based on the priority mark of the intention sequence, extracting a candidate data block set matched with the intention of each level from a distributed data storage cluster. And performing cross-modal feature alignment on the candidate data block set, and calculating the semantic coverage degree of each data block and the corresponding intention hierarchy. And screening out target data blocks according to a semantic coverage threshold, and recombining the data blocks according to a priority sequence of the intention sequence. And loading the recombined target data block set to a real-time processing channel of the voice interface to generate an interactive voice response data stream.

The invention provides a fault diagnosis-oriented intelligent question and answer auxiliary method, which comprises the following steps that: a multi-modal input processing module is constructed, and the multi-modal input processing module supports two input modes of text and voice, so that flexible acquisition of fault information is realized, and comprehensive and accurate initial data is provided for subsequent intelligent retrieval and question and answer; maintenance domain knowledge is taken as a core, a vector knowledge base supporting efficient retrieval is constructed, and a solid knowledge basis is provided for intelligent questions and answers; constructing an intelligent Agent decision module, and performing user intention recognition, task scheduling and data calling based on the intelligent Agent decision module; semantic retrieval is combined with a generative question and answer model to obtain a retrieval enhanced generative question and answer module, and multi-round reasoning and knowledge deduction capabilities of complex questions are realized; and a multi-modal feedback module is constructed, and the multi-modal feedback module converts the intelligent question and answer result into a text or voice form for feedback to adapt to the maintenance scene requirement.

The application discloses a kind of civil aircraft aerodynamic theme data management methods, belong to aerodynamics test data management technical field, the core of management method is using aerodynamic wind tunnel test train table to realize the management of test data for the basic model of civil aircraft and its research category;Managed data includes four levels of research category, research object, project and result, each level contains relevant data resources;The application includes civil aircraft aerodynamic theme data warehousing method based on train table, civil aircraft aerodynamic theme data organization management, civil aircraft aerodynamic theme data retrieval and display, civil aircraft aerodynamic theme data maintenance and civil aircraft aerodynamic theme data call.The application replaces the mode of original data organization with test condition and test state, and operation is more simple, intuitive and convenient and fast.

The present application relates to the technical field of data interaction, and provides a smart medical interaction method and system based on big data, in particular to the method, which comprises the following steps: creating a physiological knowledge data model, a user registers by inputting personal attributes through a terminal, and different permissions are given according to the personal attributes; the user inputs relevant health data through the terminal, and collects physiological data of the patient; the relevant health data is analyzed, and a weight value is given to real-time physiological parameters; the weight value is calibrated; the real-time physiological parameters are input into a disease state simulation model for simulation; the simulation result is input into the disease state simulation physiological knowledge data model, a corresponding doctor is found according to the simulation result to provide an answer, and the answer process is stored. The system comprises a health data acquisition module, a health data calling module and an interactive health data module. The present application improves the quality and efficiency of medical services, and provides a precise, convenient and personalized health management scheme for patients.

The application provides a kind of private data calling method and device based on applet, user identity information is collected and encrypted, and is packaged into unsigned digital pass; Front-end SDK checks whether there is corresponding private key, if there is user, input information to be verified and is verified by preset mode;After verification, front-end SDK and back-end SDK are signed to form signed digital pass;The whole encrypted digital pass after signing is encrypted;Data request carrying encrypted digital pass is sent to digital pass management system to obtain returned private data.In this scheme, under the premise of reasonable, legal and user authorization, the user's private data is called to the applet, more personalized content and services are pushed to the user, the user experience is improved, in addition, the security and privacy of private data in the calling process are ensured by using data encryption related technology, and the purpose of balancing user experience and data privacy protection is finally realized.

The application discloses a kind of data acquisition method and system for equipment service management platform, it is related to data acquisition technical field, it is proposed that a kind of intelligent screening reduction sequencing is used to solve the problem of low data acquisition efficiency, waste of computing resources, by collecting data call frequency, data fluctuation value, data effective period length and data area coverage range value, establish data analysis model, carry out logistic regression calculation, obtain screening evaluation coefficient, and compare with preset screening threshold value, according to the comparison result, obtain the equipment data paragraph of priority screening, then according to the data similarity of each priority screening equipment data paragraph, determine data screening paragraph, according to data screening paragraph, according to data screening paragraph call frequency user end real-time average upload speed and data screening paragraph in different area data distribution frequency degree A set of fuzzy rules are formulated to carry out fuzzy reasoning, determine data screening paragraph call sequencing result.

The application discloses a kind of carbon emission processing method and system, and carbon emission processing participant node constitutes blockchain network;Participant node includes: carbon emission monitoring platform and third-party verification agency node, the method includes: multiple monitoring devices collect carbon emission data;Edge computing gateway device obtains the carbon emission data collected by monitoring device and pushes to corresponding active identification carrier;Carrier sends industrial internet identification and carbon emission data to carbon emission monitoring platform node;Platform node generates enterprise carbon emission report according to identification and carbon emission data and sends to blockchain network;Third-party verification agency node calls carbon emission data obtained by carrier, compare the carbon emission data called with the data in report sent by blockchain network to obtain carbon emission detection result.The application can realize efficient and accurate monitoring of carbon emission based on real-time two-way access of third-party carbon emission data, which is conducive to completing carbon emission reduction task.

The invention discloses a data security traceability system and method in an oral solution medicine production process, and belongs to the technical field of medicine data security traceability. The system comprises a data traceability module which constructs an information data traceability chain based on each group of factory oral solution drugs; the source data calling module is used for calling the information data traceability chain of the oral solution medicine with the query information and marking source data; the risk analysis module is used for determining risk data of the oral solution medicine on the basis of a plurality of pieces of source data and the number of the marked query information corresponding to each piece of source data; the medicine distribution area management module is used for determining the number of oral solution medicines with risk data in each area based on the transportation data of the medicine distribution area; and the safety early warning module is used for judging whether a disease spreading risk exists or not based on the sales data of the medicine distribution area. According to the invention, abnormal data in the drug production and circulation process can be accurately locked through the traceability system, and the transparency of drug information is improved.

The invention discloses a credible data space contract dynamic generation method and device and a data calling method and device. The credible data space contract dynamic generation method comprises the steps that a natural language contract in a target scene is analyzed to obtain a key strategy element set, and constraint, behavior and environment elements are recognized to serve as corresponding class nodes; generating hyperedges to construct a three-dimensional hypergraph according to a real-time policy and node constraint logic; when a data use request signal is received, obtaining a current execution environment, a request purpose and a dynamic parameter; after the request is initiated for the first time, acquiring latest policy information from the constraint elements according to a preset interval, and updating the hypergraph into a target hypergraph; and finally, node attributes are updated based on the target hypergraph, an execution environment, a request purpose and dynamic parameters are analyzed, and an adaptive contract is dynamically generated according to an analysis result. According to the method, the contract matched with the specific requirement can be dynamically generated, and the flexibility, safety and manageability of data circulation are effectively improved.

The invention relates to the technical field of intelligent locks, in particular to an intelligent lock with an intelligent acquisition function and a control method thereof.Importance levels of corresponding acquisition functions are represented through attribute weights, then the attribute weights are corrected through data calling records, and personalized weights better conforming to user habits are obtained; then a fitness function is determined based on the personalized weight, so that an optimal acquisition function calling strategy can be found through an optimization algorithm, and the calling strategy not only can select and reject a plurality of acquisition functions according to the residual electric quantity so as to prolong standby time, but also can match user habits and reserve common and important acquisition functions of a user; the purpose of balancing energy consumption and functions of the intelligent lock is perfectly achieved, it is ensured that safety and convenience are provided, high efficiency and energy efficiency are kept, user experience is greatly improved, and good prospects are achieved.

The application provides a cross-center call chain tracking method and device, each application is monitored; when a business call request initiated by the application is monitored, first link ID monitoring log information generated by the application is output; an identification bit in the first link ID is modified based on an identification parameter in a configuration file corresponding to the application to obtain a second link ID; the business call request and the second link ID are sent to other data centers; monitoring data logs generated during execution of the business call request by the other data centers and returned based on the second link ID are received; based on the monitoring data logs, index values of each application monitoring index are calculated, and a call chain topology diagram of the application is drawn. In the scheme, the link data in the monitoring data logs generated by cross-center calling is completely returned to the data center to which the application belongs by adding an identification in the link ID, so that the data calling of the two centers is connected in series to achieve the purpose of completing the entire application call chain.

The embodiments set forth techniques for managing connections for wireless devices configured for multiple Subscriber Identity Module (SIM) environments, such as dual SIM, dual standby (DSDS) environments. A common scenario involves a first wireless device receiving a voice call (e.g., using a first SIM of the first wireless device) while carrying out a data call with a second wireless device (e.g., using a second SIM of the first wireless device). In such a scenario, the data call is often disrupted due to the voice call, which can cause confusion to a user of the second wireless device. Accordingly, the techniques disclosed herein include the first wireless device providing, in conjunction with receiving the voice call, a notification of the voice call to the second wireless device. In turn, the second wireless device can inform the user of the event to help mitigate the aforementioned confusion.

The application is suitable for the technical field of data processing, and provides a novel power system data management method. The method comprises the following steps: a first server end receives new energy power data generated by each novel power system end, and stores the received new energy power data in a classified manner; a second server end responds to a data calling request, calls new energy power data of a target category from the first server end, and stores the new energy power data of the target category in multiple storage queues; the second server end responds to a data reading request, sends the new energy power data stored in the multiple storage queues to a data reading end according to the priority order of the multiple storage queues; and the data reading end processes the read new energy power data and displays the new energy power data in a regional map, wherein the regional map contains new energy power information of each novel power system end. The application can improve the data new energy power data reading efficiency and data search time.

The invention provides a dynamic issuing strategy optimization method and system combined with a big data model, and relates to the technical field of data processing and information issuing, and the method comprises the steps: calling the big data model based on multiple types of preset data to generate a strategy feature coding result, constructing a user scene strategy dynamic response cluster, and generating an initial dynamic issuing strategy; then, applying the data to a target user group, collecting real-time data, and analyzing to generate a strategy iteration starting instruction; after a strategy iteration starting instruction is received, a strategy feature coding result is reconstructed, and an initial dynamic issuing strategy is optimized; applying the optimized strategy to a test user group, and collecting verification data to construct a strategy evolution adaptation chain; and generating a scene adaptation identifier based on the strategy evolution adaptation chain, and determining strategy application or recoding according to the identifier. According to the invention, the issuing strategy can be dynamically optimized, and the information issuing accuracy is improved.

The application relates to the field of electric communication technology, in particular to a multi-thread processing method based on a core surface target IP address, which comprises the following steps: establishing a signaling surface data packet according to a service request of a user, wherein the signaling surface data packet comprises a base station IP of a user terminal, signaling data and a target IP, the signaling data comprises a TEID of the user terminal; sending the signaling surface data packet to the base station; sending the signaling surface data packet to an edge distribution gateway by the base station; sending the signaling surface data packet to a signaling collection node for identification by the edge distribution gateway, and selecting a corresponding thread according to an identification result and transmitting the thread to a core network for data transparent transmission of a large network user; the application adopts a scheme of resource allocation by using a core network IP in a signaling learning library, ensures that a same user terminal is only processed in a same transmission thread, and avoids the problem of efficiency reduction caused by switching and data calling of different transmission threads.

The invention discloses an intelligent contract-based medical and invasive resource data calling management system and method, and relates to the technical field of data processing, and the system comprises a request uploading module, a block chain platform, a request analysis module, a data calling module and a data monitoring module. The request uploading module is used for a user to edit and upload a data calling request to the block chain platform; after receiving the data calling request, the block chain platform analyzes the content of the data calling request and performs optimal value analysis on the received data calling request by using a request analysis module to generate a processing priority table of the data calling request; the block chain platform is used for sequentially executing the corresponding data calling requests according to the processing priority table, so that the data calling efficiency is improved; and the data monitoring module is used for carrying out calling monitoring on the medical and invasive resource data of each enterprise, calculating to obtain the calling popularity of the medical and invasive resource data, and judging whether the medical and invasive resource data needs to be updated or not, so that the application value of the medical and invasive resource data is improved.

The invention discloses an AI-driven multi-source data scheduling method and system for ERP report generation, and relates to the technical field of multi-source data scheduling processing. The method comprises the following steps of: based on a received report generation demand, identifying a report type by utilizing an AI technology, and analyzing a demand data set required for completing the report; dynamically evaluating a data state based on the data behavior parameter of each piece of demand data, and carrying out data acquisition adaptive optimization processing based on the data state and the data contribution degree; in the data scheduling process, data calling self-adaptive optimization processing is carried out based on the report type, the scheduling strategy parameters of the demand data and the data state; and processing and fusing the multi-source data obtained by data scheduling after data calling adaptive optimization processing to generate an ERP report, and performing accuracy evaluation and early warning based on data accuracy parameters of the ERP report.

The application discloses a kind of data storage and acquisition method and system based on point location identification, it is related to industrial big data processing technical field.The kind of data storage and acquisition method and system based on point location identification, it includes the following steps: S1, acquisition SCADA system and the multi-source point location information and structure path information in business system, constructs point location basic information dataset;S2, based on point location basic information dataset identification point location naming structure classification state;S3, combined with classification state and the change characteristics of path field structure in historical period resolve continuity trend;S4, based on naming attribution state and path structure stability state executes conflict intensity grade assessment.The problem that the same source point of multiple systems lacks unified identification mapping, leading to component path conflict in data call process is solved.

The present application relates to the technical field of natural resource management, and particularly relates to a natural resource asset loss monitoring and early warning system based on comprehensive quality evaluation, comprising a data calling module, a layer processing module, a resource value quality index obtaining module, a primary division module, an NPP calculation module, a secondary division module, a population pressure density calculation module, a tertiary division module and an early warning module; the present application monitors the asset change of natural resources from three dimensions of resource value quality, resource ecological quality and resource pressure quality, and early warns the regions with loss risk.

The invention discloses an intelligent ship integrated control system, a data vertical correlation method, a storage medium and electronic equipment, and the system comprises a data correlation analysis module, a data collection module based on data correlation preprocessing, a ship business data calling module, and a data sharing storage module. Wherein the data correlation analysis module is used for calculating correlation indexes of vertical field data according to the similarity of the data and / or the time continuity of the data and / or the causal correlation of the data and establishing a data vertical correlation model according to the correlation indexes; the data acquisition module performs pre-association grouping on sensor data based on a data vertical association model; and the ship service data calling module calculates a ship service display result according to the indication data and the pre-associated grouped data. According to the method, the problem of low ship intelligence degree caused by poor timeliness of mass ship data analysis, service module splitting and lack of service collaboration and global optimization in the existing intelligent ship technology is solved.

The application relates to the technical field of base station survey, and discloses an intelligent terminal automatic survey data analysis and processing method and system based on deep learning, which comprises a server, an intelligent terminal and a monitoring device; the server is used for receiving base station information corresponding to each base station collected by the monitoring device; the intelligent terminal comprises a data acquisition module, a data calling module, a plant identification module and a processing module; the processing module is used for determining the base station influence degree of main plants corresponding to each base station according to surrounding environment data corresponding to each base station, plant standard growth demand information, base station basic information and base station surrounding plant growth video information; and the analysis module is used for adjusting and optimizing base station equipment corresponding to each base station based on a preset base station equipment adjustment strategy according to the base station influence degree of main plants corresponding to each base station, and outputting a corresponding base station equipment adjustment scheme.

The invention discloses an automatic quota setting method for a construction engineering quantity list project. Comprising the following steps: 1, establishing a project cost vertical class recognition model based on project quantity list data fine adjustment: data analysis, data cleaning, coding and classification, construction and formation of a project quantity list knowledge graph, standardized data annotation, generation of a training data set of a large language model, and large language model training and optimization; 2, automatic quota setting is carried out through a project cost vertical class recognition model based on project quantity list data fine adjustment, wherein project quantity list information is subjected to standardization processing, and quota knowledge graph data is called; the method comprises the steps of obtaining return items of a quota knowledge graph, performing data normalization processing, performing list grouping processing, and performing association based on normalized list feature data and a quota sub-purpose matching degree. The invention relates to the technical field of engineering cost and AI large model processing, and can solve the problem that constructional engineering pricing depends on manual operation in the prior art.

The application discloses an AI-driven multi-source data scheduling method and system for ERP report generation, and relates to the technical field of multi-source data scheduling processing. The method comprises the following steps: based on the received report generation requirement, using AI technology to identify the report type, and analyzing the required requirement data set to complete the report; based on the data behavior parameters of each requirement data, dynamically evaluating the data state, and based on the data state and data contribution degree, performing adaptive optimization processing on data collection; in the data scheduling process, based on the report type, the scheduling strategy parameters and the data state of each requirement data, adaptive optimization processing is performed on data calling; the multi-source data obtained through data scheduling after adaptive optimization processing on data calling is processed and fused to generate an ERP report, and accuracy evaluation and early warning are performed based on the data accuracy parameters of the ERP report.