52results about How to "Convenient review" patented technology

The invention relates to the technical field of intelligent operation and maintenance of mechanical equipment, in particular to an electromechanical composite transmission system self-lifting diagnosis method based on a memory sub-network, and the method comprises the steps: constructing a self-lifting fault diagnosis framework which comprises a health category prediction network, a stable information memory sub-network and a rapid information memory sub-network; in the autonomous lifting learning stage, a fault diagnosis data set A is randomly extracted, and a data set B is randomly extracted from a learned information space; predicting the data set B by using the two sub-networks, and selecting an optimal playback log; predicting the data set A and the data set B on the basis of a health category prediction network to obtain two logs; calculating the total loss based on the playback logits and the two logits of the health category prediction network, and updating the weight and the learned information space of each network; and carrying out multiple times of autonomous lifting learning until a training target is met. According to the invention, the fault diagnosis network can be continuously trained from the continuously added data streams, and the autonomous improvement of the network is realized.

The application discloses a kind of pumped storage power station multi-objective optimization scheduling method and system of water conservancy and hydropower engineering.The method comprises: obtaining the power grid regulation demand and power station operating state in scheduling window;Generation head interval under the unit operating condition reachable domain atlas, representing unit reachable operating condition and operating condition switching relationship;The regulation demand is split into regulation fragment, to find operating condition path in atlas with target response time as backtracking starting point and record path interruption event;Accordingly determine regulation gap and its physical constraint reason;Generation pre-compensation action access atlas, find compensation operating condition path again;Combined with two kinds of paths, generate multi-unit operating condition switching sequence and confirmable power scheduling trajectory.The present application can judge regulation demand bearing capacity and constraint reason in advance, correct scheduling trajectory in advance, and improve power station response certainty.

This invention discloses a method for evaluating website security protection effectiveness based on attack chain correlation analysis. The method includes: collecting request records, boundary response records, page return records, origin reception records, and processing records from the same task, and attaching the corresponding records as request events using request serial numbers; extracting the redirect address, session value, page script address, and form submission address from the boundary response records recording challenge page responses, and extracting the rewrite address, session value, page script address, and form submission address from the boundary response records recording rewrite page responses, forming a transition credential set. This invention achieves chain-like evaluation and layered judgment of website protection effectiveness through transition credential sets, attack step units, and pseudo-termination evidence rings.

The application provides a student employment assistance and behavior early warning system based on job-seeking behavior data analysis, belongs to the technical field of employment service data processing, and comprises a candidate low delivery early warning triggering module, a job opportunity verification token generation module, a delivery path pre-checking module, a job visible certificate generation module and the like; when the number of effective resume deliveries in the student platform is not higher than the delivery early warning threshold, a candidate low delivery early warning is generated first, and the job to be verified is screened based on the student employment intention and the job metadata; the job opportunity verification token is generated for the job to be verified, and the token is bound with the student, the job, the job display version, the job delivery version, the verification period and the terminal session; the pre-delivery technical conditions on the platform side are verified through the non-submission type delivery path pre-checking, and the job visible certificate is generated when the job card forms a perceivable display condition on the student terminal. The system can reduce the false positives of low delivery early warnings caused by abnormal job display, job version change, abnormal delivery path and the like.

This invention relates to the field of container loading optimization technology, and particularly to a container loading optimization method and system considering palletizing. The method includes setting container information, palletizing constraints, and cargo information; generating available pallet sizes and corresponding stack shapes; eliminating stack shapes with bottom coverage below a threshold; using the selected stack shapes to form transverse pallets that meet preset requirements; establishing a mathematical model and solving it using integer programming to obtain an initial loading scheme; performing mixed pallet loading on the remaining container space and remaining cargo, ensuring that the mixed pallet loading meets the requirements of full pallet coverage and full support; generating the mixed pallet loading result and a three-dimensional visualization model. This invention incorporates the entire palletizing-related calculation process into the optimization algorithm to solve the technical problems of cumbersome, inefficient, inaccurate, poor space utilization, and high labor costs in existing container loading calculation processes.

The invention relates to the field of infrared touch screen control, in particular to a control method and system of an infrared touch screen. The method comprises the following steps: acquiring a transmitting unit set, a receiving unit set and a forbidden list, performing topology registration and signature codebook library assembly processing, and generating a scanning configuration packet; on the basis of the scanning configuration packet, executing transmission lightening time slot sequence generation, receiving time slot sampling and dark time slot baseline deduction matching decoding processing, and generating a decoding evidence packet; based on the decoding evidence packet, baseline offset calculation is carried out, spatial form evidence and time consistency evidence generation processing is carried out, a gating evidence packet is constructed, evidence gating and anomaly classification processing is carried out, and a control output packet is generated; and extracting a verification rescanning strategy parameter from the control output packet, executing verification rescanning and passing mark generation processing, generating a rescanning result packet, and constructing a write-back update packet. According to the invention, through an evidence link and a re-scanning write-back closed loop organization, the caliber consistency and traceability of control output are improved.

The application discloses a kind of for semi-automatic generation method and system of safety and anti-seismic identification report of existing building.Method includes: extracting structural parameters from drawing by AI semantic understanding and regular check;Through mobile terminal, field data is input;Drawing parameters and field data are fused into intermediate data object;Based on SQLite specification library, applicable identification specification is automatically matched;Safety rating (Au~Du) and anti-seismic identification (first level structure check + second level bearing capacity checking) are executed;Finally, the results are automatically filled into Word template to generate complete identification report.The application is aimed at the special needs of existing building identification, integrates drawing intelligent extraction, mobile terminal edge detection and edge recording, specification intelligent matching, safety rating and anti-seismic identification and other modules, significantly improves the efficiency and standardization of identification report preparation, reduces the dependence on technical personnel experience, and is suitable for large-scale identification of existing buildings in urban renewal.

The application discloses a function function and requirement consistency verification method and system, and the method comprises the steps of obtaining a function function requirement document described in natural language, parsing the function function requirement document based on a requirement document analysis model, generating corresponding requirement semantic vectors, and forming a requirement semantic vector set; obtaining a to-be-tested function source code, performing static analysis on the to-be-tested function source code, constructing an intermediate representation, determining a plurality of code segments based on the intermediate representation, generating a code semantic vector corresponding to each code segment, and forming a code analysis result; determining a candidate matching relationship between requirement constraint units and code segments based on the vector space similarity between the requirement semantic vector set and the code semantic vector set, performing logical implication checking based on the candidate matching relationship, and forming a consistency comparison result; and determining the deviation type and deviation code segment range between the function function requirement document and the to-be-tested function source code based on the consistency comparison result.

The invention provides a road unmanned inspection system and inspection method based on multi-modal perception and a large model. The system comprises a vehicle end system used for multi-modal data acquisition, automatic driving control, real-time perception fusion and edge reasoning of a lightweight large model; the cloud platform is used for cross-modal depth identification, disease knowledge base management, GIS visual display, inspection task management and large model training iteration; the scheduling end is used for task issuing, result auditing, and visual interaction of human-aided decision making and road health assessment. On the basis of the three-layer architecture, a large model collaboration framework is further constructed, and the framework runs across a vehicle end, a cloud end and a scheduling end, is responsible for reasoning collaboration, intelligent supplementary shooting, task priority generation, structured report generation and interpretable reasoning chain construction of a multi-mode large model, and is a key mechanism for realizing closed-loop routing inspection of an intelligent collaboration system.

The invention discloses a firepower attack target distribution method and system based on a multi-constraint dynamic pointer network, and the method comprises the steps: firstly building a hierarchical model which comprises a platform layer, a target layer and a rule layer, carrying out the modeling of a data relation in collected data through employing a hyperedge based on the hierarchical model, and forming a time-varying hypergraph which is updated along with time steps; according to the method, the functions of integrally representing the capacity, the time window, the collaborative grouping, the area limitation and the fair coverage constraint in the same graph space by adopting the time-varying hypergraph and the advancement rule and timely distributing are realized; a primitive-dual online adjustment mechanism is introduced in the aspect of multi-target tradeoff to automatically allocate constraint budget for a Lagrange multiplier according to real-time violation degree, and load variance fairness and regularization are superposed, so that interpretable dynamic balance can be obtained for resource utilization, time window satisfaction, collaborative consistency and coverage balance, a security boundary can be provided, and the real-time performance of the multi-target tradeoff can be improved. And secondary selection of upper-layer strategies or players in the set can be facilitated, and the method is suitable for being widely popularized and used.

This invention discloses a multi-condition self-traceable calibration method and system for insufflators, relating to the field of insufflator metrology technology. The method includes: constructing a standard loop to apply back pressure and inject a controllable leakage; during a continuous calibration, controlling the insufflator under calibration to sequentially enter pressure stabilization, flow stabilization, and leakage disturbance conditions, synchronously collecting data through collaboratively working traceable pressure and flow references; comparing the reference measurements with the insufflator's readings to calculate pressure coupling error, flow coupling error, and dynamic response characteristics; performing standard state conversion based on preset standard pressure and temperature, fitting and generating calibration coefficients to correct the measured values, and generating a judgment result based on comparison of coupling error and dynamic response characteristics with preset thresholds; generating an automatic report including operating condition type, residual, final calibration measurement results, and uncertainty. This invention improves calibration accuracy and traceability through three-condition linkage calibration and environmental factor compensation.

The invention discloses an internet platform big data operation and maintenance monitoring and intelligent analysis integrated platform which comprises an operation and maintenance workbench, sub-platforms and a unified operation and maintenance knowledge base. The operation and maintenance workbench is used by management and operation and maintenance personnel and is used for managing the system and setting system functions; the sub-platform is used for providing full-chain operation and maintenance management and data analysis services from data acquisition, monitoring, alarm processing and standardized operation and maintenance operation to data visual analysis, knowledge management and resource configuration; and the unified operation and maintenance knowledge base is used for providing query, contribution, auditing and management of the unified operation and maintenance knowledge base. According to the invention, the integrated operation and maintenance platform integrating monitoring, management and control functions is constructed, the platform takes data as a core basis and value creation as a final target, and is tightly combined with an actual application scene, so that the data insight ability of an information department in the aspect of operation and maintenance operation is remarkably enhanced, and the operation and maintenance efficiency is improved. Therefore, the reliability of the platform and the continuity of services are ensured to a greater extent.

This application relates to a method, system, and storage medium for extracting structured data from literature. The method includes: acquiring information about the literature to be processed and information about the domain of interest; generating intent recognition routing results by calling a corresponding domain intent recognition model based on the information about the domain of interest; constructing prompt words based on the information about the domain of interest and the intent recognition routing results, and extracting first target literature information from the information about the literature to be processed; constructing a corresponding domain similarity function based on the intent recognition routing results, and generating second target literature information by removing similar literature from the first target literature information; and outputting experimental information, experimental knowledge graphs, and source relationships in a structured form based on the second target literature information. This application determines the intent recognition routing results through domain intent recognition, adaptively selects the extraction strategy and domain similarity function, and combines multimodal parsing and block processing to achieve high-completeness extraction, cross-domain adaptive fusion, and traceable structured output of experimental information from cross-domain literature.

This invention relates to the fields of medical informatics and medical big data analysis, and particularly to a full-chain integrated data system and data processing method for obesity management. The system includes the following steps: constructing a standardized obesity management data model covering the entire process of obesity from pre-diagnosis to diagnosis and post-diagnosis, forming a unified metadata architecture; receiving raw obesity management data, preprocessing it, generating standardized obesity management data, and storing it; constructing a longitudinal timeline centered on the patient, linking intervention information and indicator data at each stage of pre-diagnosis, diagnosis, and post-diagnosis, and calculating indicator changes; and generating follow-up and re-examination plans and periodic management summaries based on the event sequence and indicator changes in the longitudinal timeline, combined with preset management cycle rules and risk identification rules. This invention enables continuous integration and closed-loop management of multi-source data in obesity management scenarios, improving data integration efficiency.

This invention relates to the field of information technology, specifically to a decision tree method, execution engine, and performance optimization method and system for performance analysis. The basic principle of the solution is to propose an innovative decision tree representation method, abstracting performance expert logic into a full binary tree model, and defining it as a machine-readable decision tree definition file using a specific syntax. The branch nodes are ternary expressions containing atomic capability function calls, and the leaf nodes are parallel-executable solution expressions. The accompanying dedicated execution engine loads the decision tree into a two-dimensional array structure, calculates indices based on node execution results, and performs layer-by-layer jumps, ultimately driving the execution of the solution. This invention realizes the transformation of the performance analysis process from experience-dependent to standardized and automated execution, solving the problems of difficult knowledge accumulation, low analysis efficiency, and cumbersome or unsuitable general automation tools in existing technologies. It possesses the core effects of high readability, high execution efficiency, and strong scalability.

This invention discloses a method and system for monitoring the on-duty status of meteorological observers based on multimodal fusion and hardware-software collaboration. In this method, within a monitoring cycle, an interaction operation data of computer peripherals is collected through a behavior detection engine to determine the effective operation frequency, and facial image data is collected through a visual detection engine to calculate the percentage of effective face frames. The effective operation frequency and the percentage of face frames are input into a preset cross-judgment matrix, and the on-duty status type is output. When an abnormal status occurs, a two-level alarm is executed on an external communication terminal via serial port AT commands. Simultaneously, on-site images are captured, timestamped, and written to an encrypted log to solidify the evidence. This invention employs visual and behavioral dual-modal cross-verification, combined with a remote strong alert mechanism through hardware-software collaboration, effectively reducing the false alarm rate, ensuring timely handling of abnormal statuses, and improving the reliability and intelligence level of meteorological observation post supervision.

The application discloses an order multidimensional abnormality monitoring, recognition and comprehensive analysis system based on artificial intelligence, which comprises an order data acquisition module, a path deviation triggering module, a remark counter-evidence verification module, an order value deviation analysis module and a deviation source marking module; the system acquires basic data, remark text and actual travel trajectory of an order to be recognized, analyzes the remark text to generate a remark pointing object when the actual trajectory meets the deviation triggering condition relative to the recommended travel path, and extracts a deviation trajectory object from the actual trajectory; the remark explanation validity is calculated, the deviation degree of the order mileage, time length and amount relative to the reference interval of similar orders is combined to generate an order value deviation degree, and then a path deviation source label such as a reasonable deviation of the remark, a partial explanation deviation of the remark, an unreasonable deviation of the remark or suspected detour is output; thus, the remark text can be avoided to be directly used as a detour exemption basis, and the accuracy and interpretability of order path abnormality recognition are improved.

The invention provides an interpretable knowledge mining system, method and device and a medium, and belongs to the technical field of interpretable artificial intelligence and intelligent data mining. The system comprises a data processing module, an algorithm and intelligent interpretation module, a visual analysis module and an operation management module. An explicit mathematical model which is simple in structure and easy to understand is generated through a multi-branch shallow symbol feature learning tree structure, a dynamic branch expansion strategy, LLM guide initialization and a staged grey wolf optimization selection strategy; and an LLM and retrieval enhancement generation (RAG) mechanism is introduced to perform automatic semantic analysis and intelligent interpretation on the generated model. According to the interpretable knowledge mining system, method and equipment and the medium, the technical threshold of interpretable modeling is effectively reduced, meanwhile, the prediction performance, the structure interpretability and the knowledge discovery efficiency of the model are improved, and the interpretable knowledge mining system, method and equipment and the medium are suitable for engineering optimization, scientific modeling and cross-domain data analysis.

The application provides a three-dimensional modeling method and system based on cooperation of a mobile phone and a UAV in shooting, comprising a data acquisition module, a data transmission module, a data processing center and a model display and analysis module; the data acquisition module adopts an acquisition strategy configuration logic based on a traffic accident type and combined with an accident scene scale, and is used for determining a combination mode of acquisition equipment under different traffic accident scenes; the data acquisition module comprises a mobile phone shooting unit used for close-range data acquisition of a small-range traffic accident scene and a UAV shooting unit used for data acquisition of a large-range traffic accident. Through the cooperative acquisition mode of the mobile phone and the UAV and combined with a three-dimensional modeling processing flow, macro scene information and micro detail information can be simultaneously acquired at an accident scene, the acquisition and modeling of key elements of the accident scene can be completed in a short time, and the application is favorable for shortening the occupation time of the accident scene and improving traffic relief efficiency.

This invention belongs to the field of tunnel structural health monitoring technology and discloses a method and system for identifying tunnel structural defects and providing early warning of safety risks. The method collects surface image data, structural status monitoring data, and environmental operation data of the tunnel lining, and constructs an evaluation object dataset according to tunnel station number, monitoring section, and circumferential location of the lining. It extracts surface defect characteristic parameters such as cracks, leakage, and spalling from the surface image data, extracts structural response characteristic parameters from the structural status monitoring data, and combines historical time-series data to obtain the defect development trend and structural response change trend. It obtains the surface damage level through a defect level rule base, obtains the physical safety level through a physical assessment model, and then determines the current safety level through level envelope fusion. Based on the current safety level, development trend, environmental operation data, circumferential location of the lining, and the relationship between multiple defects, it determines the risk level and generates graded early warning information.

The invention discloses an information processing method of a content distribution network and a program product. The method comprises the steps that resource registration information of a resource registration party is received through a resource opening node, the resource registration information is stored in a block chain network, and the resource registration information is used for indicating network resource information which can be used by a content distribution network and the resource registration party of the network resource information; a content access request is received through the content distribution network, resource scheduling is performed through the content distribution network and the resource registration information, a content distribution operation corresponding to the content access request is executed based on the resource registration information, and resource scheduling information corresponding to the content distribution operation is stored in a block chain network; and calling an intelligent contract of the block chain network, and determining resource feedback information of the network resource information according to the resource registration information and the resource scheduling information. According to the technical scheme, more efficient, transparent and secure content distribution service can be provided, and the user experience is remarkably improved.

The invention discloses a face recognition access control system device based on intelligent digital registration, and relates to the technical field of information security, the face recognition access control system device comprises a personnel recognition unit, a personnel release unit and a background service unit; the personnel identification unit comprises a binocular camera, a face identification module, a feature extraction module, a data analysis module and a communication module; the binocular camera is in one-way connection with the face recognition module; the face recognition module is in one-way connection with the feature extraction module; the feature extraction module is in one-way connection with the data analysis module; the data analysis module is in one-way connection with the communication module; according to the system, the binocular camera is used for human face recognition, the position and angle of the human face can be accurately recognized under various light conditions and complex backgrounds through the stereoscopic vision principle, compared with a monocular camera, the binocular camera has higher adaptability and stability, and the safety and recognition accuracy of the system are greatly improved.

The invention provides a data development debugging method and device, equipment, a storage medium and a program product. Relates to the technical field of data development. The method comprises the following steps: in response to a received debugging request initiated by a user through a data development platform, allocating computing resources based on the debugging request and starting an interactive debugging environment instance; the debugging request comprises a Python operator code to be debugged; executing the Python operator code to be debugged in the interactive debugging environment instance, and displaying a code execution result and a variable value; and backfilling the debugged Python operator code in the interactive debugging environment instance into a static code editor of the data development platform. According to the method provided by the invention, the code execution state can be checked in real time, the code writing and debugging process is deeply integrated, environment switching and manual operation are avoided, and human errors are reduced; through a reasonable resource management and scheduling mechanism, it is ensured that computing resources can be fully utilized in the starting and running process of the interactive debugging environment instance, and resource waste is avoided.

The application provides a kind of time sequence feature and causal decoupling light weight ViT industrial hidden danger detection method in the technical field of industrial safety detection, comprising the following steps: first, obtaining industrial inspection image and preprocessing into standardized image, then constructing embedded local feature enhancement module and light weight improved Vision Transformer network, extracting enhanced local feature map;Further introduce the mechanism of physical guided causal decoupling, decompose the feature into real hidden danger, environmental interference and background residual, compare the similarity by differentiable counterfactual intervention, and output the interference discrimination reason;At the same time, cross-frame time sequence feature fusion is adopted to align continuous multi-frame features to distinguish hidden dangers and transient interference;Finally, combined with the discrimination reason, the light weight network outputs the industrial hidden danger detection result.The application has the advantages that: it greatly improves the anti-environmental interference ability, weak target perception accuracy, real hidden danger and transient interference time sequence causal discrimination ability, model explainability and end-side real-time deployment efficiency of industrial hidden danger detection.

The application relates to the technical field of artificial intelligence and legal science, and discloses a contract examination method and system based on a multi-modal large model, which comprises the following steps: obtaining an image of an original contract document and encoding the image into a unified multi-modal feature representation that fuses text semantics, visual elements and their spatial coordinates; based on the structured rules in a contract examination knowledge base, extracting a feature subset related to the rules from the unified multi-modal feature representation and performing cross-modal reasoning; generating potential rule violation items and their supporting multi-modal evidence segments; for each potential rule violation item, checking the reliability of the evidence segments and generating a final examination result. The application realizes end-to-end joint modeling and understanding of contract text, visual elements and their spatial layout, can automatically, accurately and interpretively identify form and content violations of a contract, and significantly improves the accuracy, automation level and operability of contract examination.

The present application relates to a kind of port engineering design report proofreading method based on large language model, including the following steps: PDF or DOCX format design report is parsed, and unified structured content list is generated;According to the chapter segmentation and ordering storage of title hierarchical feature to structured content;The specification name involved in section is extracted, non-engineering specification file is filtered, and its state information is inquired in specification standard database;According to different proofreading task and checking task, different large language model is called to process, and structured result containing modification suggestion, reason, text space coordinate and table error index is generated;For PDF format document, proofreading result is mapped to page display area and highlighted to show;According to proofreading result, annotated DOCX file or PDF file is exported.The present application can improve the proofreading efficiency of port engineering design report and the accuracy of specification reference checking and problem positioning.

The application discloses an electrician safety training method and system based on virtual reality interaction, relates to the technical fields of virtual reality interaction data processing, virtual scene state control and electrician safety training, and discloses the following technical scheme. A training control end establishes a training session, reads device topology, state changes, contact areas, interaction collection and time reference versions, loads state snapshots and safety operation units; collects pose, virtual tool state and contact data to form an interaction evidence segment; operation candidates and state maintenance intervals are formed according to state snapshots corresponding to action start time and action completion time; the target object, contact area, virtual tool, grabbing state, contact duration and safety premise state of the candidate are verified, and it is verified that the safety premise state in the state maintenance interval has not changed; when the verification is passed, a safety operation closing record is registered, the device state is updated, and subsequent operation qualifications are approved; when the verification is not passed, the current state is maintained, and the reason for the failure is registered.

This application belongs to the interdisciplinary field of computer application technology and aerospace equipment technology, and specifically relates to an intelligent technical document compilation system and method based on evidence constraints. The system includes a data governance module, a compilation constraint graph construction module, an automated generation module, an intelligent review module, an intelligent retrieval module, a change impact analysis module, and an interface integration module. The system converts multi-source equipment technical data into source record objects, chapter unit objects, and evidence objects, constructs a chapter constraint graph, and generates chapter task packages containing template skeletons, mandatory entities, mandatory parameters, and evidence sets. Based on this, it outputs initial drafts of the document with evidence identifiers, and forms candidate release versions through rule review, graph consistency review, and semantic review. When the technical status changes, it identifies affected chapters and recompiles them accordingly. This invention improves the traceability, consistency, and timeliness of technical document compilation, review, retrieval, and updating.

The invention belongs to the technical field of vascular navigation and deep neural network modeling, and provides a vascular navigation path planning method based on deep reinforcement learning. The method comprises the following steps: firstly, constructing a vascular navigation state action model by unifying a coordinate system, dividing a safety corridor and binding a state action index; configuring parameters of a strategy network, a value network, an experience playback buffer area and a soft target network to form a training preparation structure; training to obtain a convergent navigation model through multiple interaction rounds in combination with composite reward calculation and parameter updating; finally, candidate paths are generated, and deployable vascular navigation configuration is output through screening, instruction resampling and parameter packaging. According to the method, the safety, efficiency and control smoothness of path planning can be effectively improved, vessel wall collision is avoided, the method adapts to a complex vessel branch environment, and the reliability and adaptability of robot navigation are enhanced.

The invention discloses a molecular structure-activity relationship modeling method based on symbol regression KAN, and belongs to the field of chemoinformatics. The method comprises the following steps: constructing and cleaning molecular property data to form a molecular-chemical descriptor-target property data set; calculating and screening descriptors, and reducing redundancy and colinearity by adopting variance screening and correlation analysis; and training the KAN to obtain a target property prediction function and exporting an explicit expression. By taking the organic amine CO2 absorption cycle period as an example, the upper / lower limit auxiliary screening of the cycle period can be predicted. According to the modeling method, an interpretable basis is provided under a small sample condition, and the dependence on a large amount of experimental data is reduced.