104results about How to "Guaranteed traceability" patented technology

The invention relates to the technical field of industrial enterprise carbon data management, and discloses an industrial enterprise supply chain carbon footprint economic accounting and management method for a dual-carbon target, and the method comprises the steps: selecting and obtaining a public high-frequency economic agent signal based on a technical premise that core factors for driving industrial product price and carbon emission intensity have homology, dynamically correcting the static reference emission factor through a relevance conduction model; according to the method, a public economic signal is utilized to avoid a traditional mode of relying on static lagging data, the technical problem that the real dynamic state of the carbon intensity of the supply chain cannot be sensed is solved, and the real dynamic state of the carbon intensity of the supply chain can be sensed. The almost real-time carbon risk situation sensing ability of an enterprise is improved, and passive bookkeeping after carbon management is engaged is converted into active intervention fused into daily business.

The invention relates to the technical field of riverway desilting, in particular to a riverway self-adaptive desilting system and method based on intelligent water level perception, and the method is executed by a central control unit and comprises the four steps of model construction and benchmark calibration, real-time monitoring and siltation diagnosis, precise survey and operation planning and closed-loop execution and model synchronization. The system comprises a central control unit, a water level intelligent sensing array, terrain scanning equipment and dredging machinery, according to the method, the three-dimensional digital riverbed model is constructed, the sedimentation state is dynamically judged in combination with the water level sensing data, an accurate desilting operation scheme is generated, and operation closed-loop control is achieved. According to the method, navigation and ecological riverway dredging requirements are considered, the dredging precision and automation level are improved, the operation cost is reduced, intelligent transformation of riverway management is promoted, and an efficient solution is provided for long-acting treatment of the riverway.

The invention discloses an intelligent demand analysis and man-hour evaluation method and system, and belongs to the technical field of computer vision and artificial intelligence. Analyzing the multi-modal demand document containing the text, the picture and the table to generate structured demand data; based on the structured demand data and the system module description, performing module-level splitting on the demand to generate a module task set; retrieving an associated system implementation context for each task in the module task set based on a multi-dimensional knowledge base; fusing the structured demand data, the module task set and the system implementation context to generate a fine-grained technical task; based on a historical case index, calculating reference working hours for the fine-grained technical task; and cross-module cooperative correction and personalized correction based on the ability of the task executor are sequentially performed on the reference working hours to obtain final evaluation working hours, so that automatic deep analysis and accurate and personalized working hour evaluation of software requirements can be realized.

The invention discloses a Linux-oriented vulnerability repair verification method and system and a medium. The method comprises the steps of creating a test application form for a CVE vulnerability patch in a task management system, preparing a test environment for CVE vulnerability repair verification as well as a required test table, a software source and a test strategy file, and calling a tool interface to automatically trigger an assembly line; the assembly line executes the test suite in the test environment based on the test table, the software source and the test strategy file and collects an execution state, and if the execution state is failure, automatic retry can be carried out on the CVE vulnerability based on manual triggering; and finally, generating a report file, writing a verification result for the test application form in the task management system, and if the verification result is that verification is passed, issuing a service pack of the CVE vulnerability. The invention aims to realize efficient, traceable and extensible Linux vulnerability repair verification, realize full automation and intelligence of the vulnerability verification process, and improve the accuracy, traceability and expandability of verification.

The present application relates to the technical field of network security, and more particularly to a cloud platform vulnerability real-time quantitative analysis system based on a dynamic knowledge graph, which comprises a multi-source heterogeneous data acquisition unit, a dynamic knowledge graph construction unit, a vulnerability quantitative evaluation unit, an intelligent response disposal unit and a visual verification unit.The vulnerability quantitative evaluation unit identifies the possible propagation path of the vulnerability through an improved weighted breadth-first search algorithm, and introduces a real-time relationship weight and a path attenuation mechanism.The present application can improve the accuracy of vulnerability propagation path identification and the accuracy of risk level quantification by generating dynamic relationship edge weights through a real-time weight calculation module, combining a path attenuation processing module to adjust the weight of long-term non-vulnerability propagation correlation, and cooperating with the weighted breadth-first search algorithm to identify the vulnerability propagation path, thereby effectively solving the problem that traditional risk assessment relies on static parameters and is easily disturbed by invalid paths.

This invention discloses an individual motion behavior analysis system based on dynamic modal configuration and rule-guided fusion, belonging to the fields of intelligent perception, sports science, and human-computer interaction. It includes a data input module, a dynamic modal organization and configuration module, a multimodal feature modeling and fusion module, an indicator-level evaluation and behavior state prediction module, a statistical rule-guided analysis and result correction module, and a structured result generation and output module. These modules work together to form a complete closed loop for motion behavior analysis technology. This invention aims to address the problems in existing motion behavior analysis technologies, such as limited dimensionality of single-modal information, rigid multimodal fusion methods, insufficient stability and interpretability of analysis results, and strong dependence on large-scale manually labeled data.

The invention discloses a supply chain full-process traceability tracking method based on a block chain, and relates to the technical field of block chain and supply chain traceability, and the method comprises the specific steps: collecting supply chain node identity qualification basic information, and carrying out the structural processing; generating a unique initial dynamic chain code by using an encryption algorithm, and storing the unique initial dynamic chain code in a main chain after binding the unique initial dynamic chain code with qualification information hash; integrating the collected data into traceability data and checking node identities and chain codes; after the verification is passed, the traceability data is bound with a chain code for the second time, and a timestamp is added for chaining; updating the chain code according to the service state, adding an identifier to the old chain code and permanently storing the identifier; according to the invention, a rigorous node identity authentication system is constructed, so that the credibility of a traceability subject is guaranteed, and identity and qualification data can be traced and verified in the whole process; multiple terminals collect data cooperatively, completeness and timeliness are ensured through multiple associations, chain code dynamic update adapts to service changes, and data association continuity is ensured; the whole-process mechanism effectively solves the problem of traditional traceability data splitting.

The invention discloses a flexible manufacturing-based DPA component matching method, which comprises the following steps of: establishing a DPA component requirement catalog, establishing a management database, and creating catalog entries for each component needing DPA detection; the method comprises the following steps: establishing DPA components, and creating a corresponding DPA component for each basic component needing to execute DPA detection in enterprise product bill of material structure management; the method comprises the following steps: establishing a corresponding relation between a DPA component requirement directory and a component, establishing a mapping relation between a DPA requirement directory and a DPA component, triggering to generate or call a corresponding DPA component demand according to the mapping relation, and realizing automatic conversion from a detection requirement to a specific execution material; and establishing a matched operation system, and integrating the system into a manufacturing execution system or a material demand planning module of an enterprise resource plan. According to the method, automatic identification of DPA detection requirements, intelligent matching of detection materials and accurate accounting of related cost can be realized.

The application discloses a kind of data disaster recovery methods of supporting multiple backup path switching, comprising, based on the sensitivity of input data and the generation of dynamic granularity data slice of storage medium characteristics, and generate the metadata label containing data slice identification, storage preference and recovery priority;Path quality atlas is generated for each data slice by constructing heterogeneous transmission path performance model through metadata label, and optimal transmission path is allocated, and path performance is monitored;Abnormality is detected and migrated slice by the standard deviation of cumulative transmission delay;Incremental integrity verification and Merkle proof of blockchain storage are used for parallel checking, and retransmission is preferentially checked failed slice;The application ensures the reliability and stability of data disaster recovery through the synergistic cooperation of dynamic data slicing, backup path optimization and recovery verification, to meet the real business needs.

The invention belongs to the technical field of software engineering, and particularly relates to a probe generation method, system, equipment and medium for model coverage analysis, and the method comprises the following steps: traversing source codes of a whole model to identify operators needing instrumentation; aiming at each operator, generating a mapping file carrying a unique identifier according to a logic path recorded in the operator; wherein the mapping file defines a mapping relationship between the coverage state of each logic path and the bit of the integer value in the log entry; and generating one or more probes according to the number of logic paths recorded in the mapping file, and modifying source codes of the model according to source files of the probes to realize automatic instrumentation. According to the method, pre-compiling is not carried out during instrumentation, one or more probes with accurate matching interfaces are dynamically generated according to the monitoring requirements of a specific model, and compared with a limited preset traditional scheme, the number of the probes can be infinitely increased, and the actual requirements are met.

The invention provides a stator outer diameter roundness detection mechanism and method based on internal expansion type positioning, and relates to the technical field of precision measurement, the stator outer diameter roundness detection mechanism comprises a base station, a rotation driving module, a product positioning module, a lifting driving module and a detection module, the product positioning module adopts an internal expansion type mechanism composed of a top column, a positioning block and a wedge block group, the wedge block group is driven to radially tighten the inner hole of the stator through the axial movement of the top column, so that different inner diameter tolerances are adapted, high-precision and non-eccentric positioning is realized, during detection, the lifting driving module drives the plurality of contact displacement sensors to move along the axial direction of the stator and scan the outer diameter contour of the stator iron core unit, and meanwhile, the rotating driving module is used for indexing, so that the detection precision is improved. According to the invention, automatic and high-efficiency detection of the outer diameter roundness of all stator core units is realized, the problems of inaccurate positioning and poor universality of a traditional jig are effectively solved, and the detection precision and efficiency are remarkably improved.

The invention relates to the technical field of building curtain walls, in particular to a temperature control adjusting system and method for a breathing type curtain wall, and the system comprises an inner circulation module which is used for guiding indoor air into a cavity of the breathing type curtain wall and returning the indoor air after heat exchange; the outer circulation module is used for guiding outdoor air into the cavity of the breathing type curtain wall, carrying out heat exchange and then discharging the outdoor air; a data acquisition module; a data processing module; the control module is used for judging whether the temperature control of the room meets a preset standard or not according to the temperature control stability characterization value; and the optimization module is used for determining a temperature control optimization strategy when the temperature control of the breathing type curtain wall does not meet a preset standard according to the current deviation degree of the room with the abnormal temperature and secondarily determining the temperature control optimization strategy of the room with the abnormal temperature according to the indoor interference characterization value of the room with the abnormal temperature. The temperature control efficiency of the breathing type curtain wall is improved.

The invention relates to a multi-mode communication interface adaptive remote upgrading system and method based on a multi-source heterogeneous sensor. The system comprises a cloud management platform, a comprehensive processing unit, an acquisition unit cluster and a sensor terminal, each acquisition unit cluster is connected with sensor terminals of different sensor types through various heterogeneous interfaces; under the condition that the cloud management platform judges that the target sensor terminal exists in the sensor terminals, a pre-stored equipment upgrading file is issued to a comprehensive processing unit; the target sensor terminal meets a device upgrading condition corresponding to a pre-stored device upgrading file; the comprehensive processing unit dynamically instantiates a plurality of transmission channels and issues an equipment upgrading file to each acquisition unit cluster; the acquisition unit cluster issues the equipment upgrading file to the target sensor terminal; and the target sensor terminal executes firmware upgrading operation based on the equipment upgrading file. By adopting the method, efficient firmware upgrading can be carried out on the sensing communication equipment.

This invention relates to an automatic detection system and method for elevator landing door locking devices. The system includes a moving base mounted on the car top, a door lock drive mechanism driven by the base, an image acquisition device, a signal acquisition device, and a control device. The door lock drive mechanism has two roller push plates that can move independently or collaboratively, enabling adaptive driving of single-action or double-action roller door locks. The image acquisition device acquires door lock images to identify door lock features and the lock hook. The signal acquisition device acquires the door lock safety circuit break signal. The control device automatically controls the drive mechanism based on the identification results and triggers visual measurement upon receiving the break signal to calculate the lock hook engagement depth and determine whether it meets safety requirements. This invention achieves automatic, accurate, and efficient detection of door locks with various structures, replacing traditional manual methods and significantly improving the objectivity, accuracy, and applicability of the detection.

The invention provides an intelligent identification method for an illegal opening behavior of a box body, and relates to the technical field of data processing, the method comprises the following steps: monitoring physical state data of the box body in real time, the physical state data comprising a vibration signal, an opening and closing state signal and position information; performing feature extraction through the physical state data to obtain an initial behavior feature sequence; based on the behavior characteristic sequence, three specific structure points on the surface of the box body are dynamically selected as a group of reference positions, and the specific structure points comprise a box body lock installation point, a box body hinge connection point and a box body seam monitoring point; according to the selected three specific structure points, constructing a dynamically changing area range; performing partition analysis on the dynamically changed region range to obtain a plurality of sub-regions; and obtaining a behavior characteristic correction coefficient according to the dynamic change characteristic of each sub-region. The illegal opening behavior recognition precision is improved, and the false alarm rate and the missing report rate are reduced.

The invention discloses a query response and code generation method and system based on power field document analysis, and the method comprises the steps: carrying out the analysis and preprocessing of an input field document, and constructing a document text logic diagram; constructing a domain knowledge graph; receiving user query, and executing structure matching retrieval based on a document text logic diagram and association reasoning retrieval based on a domain knowledge graph to form a traceable evidence packet; constructing a structure enhancement context based on the evidence packet, inputting the structure enhancement context into a domain language large model, and generating a response containing a natural language description and a structured domain language code; and performing instant compilation and tensor simulation verification on the structured domain language code, triggering retrieval and generated closed-loop correction based on deviation information when the verification is not passed, and outputting an analysis result and the code when the verification is passed. According to the method, the accuracy, interpretability and output reliability of long document processing in the electric power field are improved.

The invention belongs to the technical field of offshore wind power operation and maintenance and reliability engineering, and discloses an offshore wind turbine generator system-level health degree evaluation method based on dynamic weight distribution, and the method comprises the following steps: S1, collecting and preprocessing the multi-source data of an offshore wind turbine generator; s2, constructing a layered health degree evaluation index system; s3, fusing the mechanism model, the data driving model and the statistical reliability model, and constructing a subsystem degradation model to obtain a subsystem health degree; s4, performing weight fusion in combination with the static weight and the dynamic correction factor to obtain a dynamic weight; s5, fusing the subsystem health degree and the dynamic weight to obtain a system-level health degree; and S6, performing confidence interval sorting and risk grade division according to the system-level health degree. According to the evaluation method provided by the invention, through fusion of a mechanism model, a data driving model and a statistics model, the physical interpretability is reserved, the fitting capability of nonlinearity and coupling degradation is improved, and the misjudgment and missed judgment risks are reduced.

The application belongs to the technical field of artificial intelligence and information security, and provides a large model full-link process data evidence management method and device, computer equipment and computer program products, which collect data by embedding a tracking probe in the large model full-link processing flow, record the derived parent-child relationship, store detailed data, calculate a cryptography hash value and upload a blockchain, perform reverse graph traversal query to obtain a traceability chain, and perform desensitization processing and signature output. The method solves the problems of missing data blood relationship record, easy tampering of evidence chain, low audit efficiency and data association rupture in the prior art, has the advantages of realizing structured evidence management of large model full-link process data, ensuring the traceability of data sources and the integrity of evidence, improving the audit efficiency and credibility, and meeting the supervision requirements.

This invention provides a data supervision method, apparatus, electronic device, and storage medium. The method includes: obtaining a subset of evidence storage requirements corresponding to the business system from a set of evidence storage requirements based on the attributes of the business system, and sending the subset of evidence storage requirements to the business system, so that the business system generates evidence storage information of the supervised data based on the operation log of the supervised data and the subset of evidence storage requirements during the flow of supervised data; receiving the evidence storage information of the supervised data returned by the business system, and analyzing the evidence storage information to obtain analysis results; based on the analysis results, determining whether there are any anomalies in the flow of supervised data, and if there are anomalies, identifying the abnormal nodes based on the evidence storage information, and handling the abnormal nodes to obtain handling results. This invention, by collecting information at relevant nodes in the data flow and aggregating and storing it level by level, can form a multi-layered collaborative supervision, thereby achieving self-supervision of the entire network.

The application relates to a network fault processing method and device for an automobile production line and electronic equipment, wherein the method comprises the following steps: obtaining a request response result of a research and development end key generation system; judging whether communication between the current production line and the research and development end key generation system is interrupted based on the request response result; in the case of communication interruption, obtaining any offline key meeting a preset availability condition from a pre-deployed backup key pool; filling any offline key into a target electronic control unit of a current vehicle, and recording the offline key binding relationship between any offline key and the current vehicle, so that the offline key binding relationship is sent to the research and development end key generation system after the communication between the current production line and the research and development end key generation system is restored. Therefore, the technical problem that, in the related art, the emergency capability is poor, the production line is stalled under the condition that the network connectivity is poor, and the production efficiency and delivery progress are affected is solved.

The embodiment of the invention discloses a data processing system of a dense array and a device thereof. The data processing system of the dense array comprises an equipment unit which comprises an array and a mobile communication device, and the array is composed of seismometers of different models; the acquisition unit is used for providing a gateway for data synchronization and information transmission of the mobile communication equipment and providing a format conversion tool for ensuring that data is transmitted according to a unified format; the data unit is used for providing unified data access, data management and index management for multi-source heterogeneous data, and providing data whole-process management and access such as data acquisition, management, archiving storage, query access and the like; the software function unit is used for carrying out standardization processing on the data in the data unit and carrying out task management on array layout in the equipment unit; and the application unit provides a plurality of platform products according to the functions of the data unit and the software function unit.

This invention provides a privacy protection and access control method and system based on unstructured metadata, relating to the field of data processing technology. The method includes acquiring time-series metadata from multiple data source nodes, calculating sensitivity features and scores, and classifying sensitivity levels; allocating differential privacy budgets for processing according to sensitivity levels; setting tiered access permissions and anonymizing visitor information; analyzing access behavior characteristics and setting differential privacy thresholds for abnormal access detection. This invention achieves refined tiered protection for time-series sensitive data, improving privacy protection efficiency while ensuring data availability.

The invention provides a psychological counseling system and method based on artificial intelligence, and relates to the field of intelligent psychology, comprising session node management, trust state management, observation management, antagonistic narrative management, self-organizing treatment, and asymmetric override and permission and auditing combined scale block cooperative operation. The traceability and credible management of the whole psychological consultation process are realized; the system generates an auditable session node and gives a trust state identifier at the end of each session, and a qualified observation chain is formed through user clear interaction to trigger trust judgment; the antagonistic narrative module generates an anti-narrative according to an ethical rule and collects a user structured response as a trust evidence; the self-organizing treatment module automatically executes node classification and opens artificial recheck when a critical condition is met; the override and permission module introduces an independent override to examine the trust and ethical compliance of the promotion node; the auditing module writes all events into a non-tampering account book and triggers responsibility tracing when a rule is violated; temporary intervention can be executed through multi-party rechecking in an emergency situation so as to guarantee the safety of a user.

This invention relates to a method for patent retrieval and technology monitoring of multi-source heterogeneous data. It constructs a multimodal semantic representation including text, images, and time-series fragments, and generates a joint temporal representation vector by combining attention perturbation entropy and term evolution distance. A unified semantic space is established based on historical technology anchors, dynamically monitoring and quantifying semantic shifts to achieve real-time determination of drift trends. When substantial semantic drift occurs, local semantic correction is performed using gated contrastive learning and an anchor-aware adaptation layer to guide the orderly alignment of newly added modal features, ensuring the continuation and expansion of the original semantic topology. Simultaneously, an anchor decay and candidate new anchor generation mechanism is designed, combining cross-validation from patent citations, industry reports, and policy documents to achieve incremental expansion of the semantically stable anchor set. This scheme effectively improves the fusion accuracy, real-time adaptability, and dynamic topology update capability of multimodal patent data.

The invention relates to the technical field of data management, and provides a lightweight business data change history recording method and system.The method comprises the steps that data persistence operation initiated through an ORM framework is intercepted and analyzed, and the operation type, involved target business objects and corresponding operation conditions of the data persistence operation are determined; reading external dynamic configuration, and judging whether the target business object is set as an audit object which needs to record a change history according to configuration information; and for the audit object needing to record the change history, automatically executing data state capture and audit log generation corresponding to the operation type. According to the method, the development efficiency can be remarkably improved, the maintenance cost can be remarkably reduced, non-invasion and purity of service codes are achieved, high flexibility and expandability are provided, integrity and traceability of audit data are guaranteed, and system operation and maintenance and data governance experience are optimized.

This invention discloses a multi-tenant end-to-end data security isolation and control system and method, belonging to the field of vehicle network data security. It aims to solve the problems of easy data crosstalk, discontinuous isolation, unreliable trust benchmarks, and difficulty in compliance traceability in multi-tenant scenarios. The system generates a tenant root identifier (TID) for vehicle enterprise tenants, which, together with the device sub-identifier (DID), forms a tenant identifier chain. This chain is synchronized with a trusted authentication center to establish a vehicle-cloud hardware-level trust root. When the vehicle terminal accesses the system, it completes two-way identity authentication and allocates a dedicated message queue telemetry transmission MQTT topic partition and access permissions according to the TID. The terminal collects time-series vehicle control data and generates encrypted data frames with intrinsic identifiers and checksums for uploading. The access gateway performs dual isolation verification before transparent transmission. Data is forwarded to an independent logical storage partition for isolated storage according to the TID. This invention achieves strong hardware-level isolation, real-time verification, and full traceability throughout the entire end-to-cloud chain, effectively preventing cross-tenant data leakage.

The invention discloses a substance exploration scheme iterative generation system and method, and relates to the technical field of substance exploration scheme generation. The material exploration scheme iteration generation system is provided with a Controller layer, a Service layer, a robot and workstation gateway, at least one workstation, at least one robot, a DAO layer and an algorithm analysis and parameter optimization module. According to the invention, full-process automatic closed loop from task parameter submission, instruction generation, equipment cooperative execution, data storage to model training and formula prediction is realized, manual intervention is not needed, manpower input and material consumption are reduced, experiment efficiency and result accuracy are improved, traceability of experiment data and system stability are guaranteed, and the system is suitable for large-scale popularization and application. The problems that in a traditional material science experiment, manual experience is relied on, task issuing and instruction conversion efficiency is low, errors are prone to occurring, experimental data collection and analysis are lagged, and parameter optimization lacks an automatic mechanism are solved.

The invention provides an electrical parameter measuring device and method for a rock and soil sample. The device comprises a device base, a horizontal holder assembly, a pressure assembly, an AB power supply electrode assembly, a top end M and N spring electrode assembly, a lateral MN probe electrode assembly and an electrical parameter measuring module. Two horizontal clamp assemblies are symmetrically arranged on the left side and the right side of the device base, pressure assemblies are installed on the horizontal clamp assemblies and abut against the AB power supply electrode set, the top end M and N spring electrode assemblies are installed at the two ends of the middle of the device base and stretch across the device base, and the lateral MN probe electrode assembly is installed on the rear side of the device base. And the electrical parameter measuring module is connected with an electrode column on the device base. The technical problems that in a traditional method, clamping force is difficult to control, contact is poor, current distribution is uneven, the process is opaque, data cannot be post-processed and the like are solved, and universalization, high precision and repeatable measurement of rock and soil samples are achieved.

The application discloses a kind of lithium battery fault intelligent diagnosis method based on deep learning, comprising the following steps: collecting lithium battery operating data and carrying out quality correction, obtain operating data set;Input to operating condition perception model generates multi-scale feature vector representing different operating states;Initial fault diagnosis model is obtained by initial fault class label, initial fault probability value and diagnostic feature vector;Form uncertainty feature vector set by confidence evaluation;Perform bidirectional backtracking correlation analysis, extract associated time period operating data subset;Diagnosis is carried out again, generates review result and carries out consistency comparison with initial result;Conflict result generates conflict mode information and is stored to fault mode library, without conflict when directly output final diagnosis result;The diagnosis result of new data is corrected using fault mode library Pattern matching, output corrected final diagnosis result.The application can significantly improve fault detection rate, reduce misjudgment rate and shorten diagnosis duration.

The present application relates to a kind of phytoplankton imaging flow trait analysis method and system, wherein the method comprises: the single particle image exported by imaging flow cytometry equipment is defined as a phenotype object to be analyzed;From the JPEG annotation section of single particle image, corresponding optical signal field of phenotype object is obtained by byte analysis;Phytoplankton target region segmentation is carried out on single particle image, and phytoplankton target mask is obtained;The two-dimensional morphological characteristics of phenotype object are calculated based on phytoplankton target mask;Two-dimensional morphological characteristics and optical signal field are bound in corresponding phenotype object, and event-level morphological-optical fusion trait vector of phenotype object is generated, and event-level morphological-optical fusion trait vector is output.Using the present application, image morphological information and optical property information are synchronously acquired and fused from the same data source, and the acquisition efficiency of phytoplankton single particle comprehensive characteristics is improved.