102 results about "Historical record" patented technology

The application provides a cognitive diagnosis method and system based on causal inference to eliminate problem difficulty bias, relates to the technical field of educational data mining, and specifically includes the following steps: preprocessing the historical record of a student's answer to a problem to obtain a training set composed of a student, a problem, problem difficulty and a score; introducing a problem difficulty variable on the basis of an existing diagnosis model, eliminating bias by using causal inference, constructing a cognitive diagnosis model, and training the cognitive diagnosis model by using the training set; inputting a student to be diagnosed, a problem and problem difficulty into the trained cognitive diagnosis model to obtain a cognitive diagnosis result of the student output by the diagnosis model; the application provides a general cognitive diagnosis framework, creates a cognitive diagnosis model based on an existing diagnosis model, eliminates the adverse effects of problem difficulty bias by using causal inference technology, and performs unbiased training on the model to diagnose the cognitive level of the student, thereby improving the accuracy and efficiency of cognitive diagnosis.

The application discloses a digital thread driven intelligent management system for a clinical laboratory, which comprises a system body, and the system body is operated through the following method, and the specific method comprises the following steps: obtaining patient historical records and same batch sample data from a pre-established database by collecting current test result data, and obtaining multimodal information containing original images, detection curves and trend deviations; determining potential abnormal patterns by processing the original images and the detection curves through an abnormality detection algorithm according to the multimodal information; if the abnormal patterns are inconsistent with historical comparison results, comparing previous results of the patient through a trend analysis algorithm to judge the trend deviation degree; obtaining critical project specific threshold values according to the trend deviation degree to obtain key clue recognition results; and the application aims to solve the problem that in the prior art, when facing critical value projects, comprehensive verification and rapid release cannot be balanced, resulting in poor quality control and efficiency of the clinical laboratory.

The application relates to the computer technical field and discloses a precision inspection method and system based on a multi-dimensional green pass image, aiming to solve the problems of low efficiency, high artificial dependence, inaccurate fee evasion identification and the difficulty in balancing the traffic experience and supervision in the existing green pass vehicle inspection. The method comprises the following steps: acquiring vehicle static information, cargo images, travel paths, historical records and environment perception and other multi-source data; after being structured, cleaned and aligned, a green pass image covering four-dimensional features of vehicles, cargos, travel and behavior is constructed; a pre-trained multi-layer fusion inspection decision model is inputted, and a risk score and an inspection level suggestion are outputted, and the inspection strategies of exemption, image review or opening-box inspection are executed in parallel. Through a cross-dimensional attention mechanism and online incremental learning, high-precision, self-adaptive and intelligent inspection is realized, and the efficiency and fairness are significantly improved.

The application discloses a kind of for foundation pit peripheral building settlement safety monitoring method and system, it is related to safety monitoring technical field, the method includes the following steps: presetting foundation pit peripheral building monitoring index, data is collected and summarized as settlement monitoring history record;Arbitrarily select a historical record and its monitoring index, extract its time window in corresponding time series change curve, pre-process to obtain trend form vector and construct monitoring characteristic trend set;Presetting template library, calculate similarity, reach standard and determine that both match;Collect each working condition normal record to form characteristic sample set, calculate the variation coefficient and weight of single point and space-time correlation characteristics and normalize;Calculate deviation degree and comprehensive health index for the record to be evaluated, determine early warning threshold, real-time identification working condition, calculate real-time health index, according to early warning grade threshold interval executes early warning operation, the application realizes the safety monitoring of foundation pit peripheral building settlement.

A comparative editing workflow streamlines drafting by leveraging structured datapoints extracted from multiple matters. After generating normalized values and citations for a current and a prior document set, the system may display the datapoints side by side so differences are apparent. When a user clicks a datapoint in the current matter, a drop down list of candidate values may be dynamically populated from the prior matter and allowable categories; the user may select one of these values or enter a custom value. The platform may locate all instances of the datapoint in the current documents using stored citations and automatically replace them with the chosen value, update the structured record, reextract dependent fields where necessary and preserve version histories. The updated document and datapoints may then be presented for review.

The application provides a dynamic monitoring and optimization method and system of an artificial intelligence sandbox environment, relates to the technical field of artificial intelligence safety, and comprises the following steps: obtaining execution state data of a model, constructing a directed dependency graph for abnormality identification and propagation analysis, and generating an abnormal feature vector. Root cause information is extracted based on the vector, resource demand is predicted through historical record clustering, adjustment demand is generated, the demand is corrected through loop dependency analysis, and adjustment components are divided. Finally, the resource allocation ratio is solved by comprehensively analyzing multi-model information, and environment optimization instructions are generated. The application realizes accurate positioning, root cause analysis and dynamic optimization of abnormal behaviors in the sandbox, and improves monitoring efficiency and resource utilization.

Increase the amount of learning data about users based on their behavioral history. [Solution] The information processing device (10, 10a) includes an input means (111) for inputting a prompt to a first large-scale language model that includes historical information relating to the user's behavior history and facility information relating to one or more facilities; an acquisition means (112) for obtaining a response from the first large-scale language model indicating whether or not the user will visit one or more facilities; and a generation means (113) for generating training data for machine learning of a model different from the first large-scale language model based on the historical information and the response.

The current document is directed to methods and systems that automate generation and storage of documentation and intermediate results produced during computational-model-generation processes. In described implementations, a listener process is established within development-environment components of a data-science pipeline. Each listener detects data-collection events and automatically stores information extracted from the development environment in which it is established. The automatically stored information is processed and aggregated, along with various intermediate products and results and / or references to the intermediate products and results, for forwarding to a backend process that analyzes and further processes the forwarded information for storage in a centralized database. The centralized database can be subsequently used to provide a detailed history of the steps carried out in a data-science pipeline and to reconstruct data-science-pipeline states at specified time points and to generate evidentiary records or reports suitable for compliance and audit purposes.

The application relates to the technical field of pipeline data management, and discloses an oil and gas station pipeline whole life cycle data management method and system, which comprises the following steps: extracting pipeline geographic information, extracting spatial correlation features through a graph neural network, combining pressure time sequence data to determine a pipeline conduction mode through a preset long short-term memory network; quantitatively evaluating the conduction mode according to historical maintenance and abnormal data, extracting topological nodes if the value exceeds a threshold, combining a preset attention mechanism to obtain a space-time coupling vector; extracting node correlation features from the space-time coupling, quantitatively fusing to obtain a heterogeneous node set, generating an abnormal atlas through graph convolution; extracting risk indexes, if upstream conduction effects are shown, obtaining a damage prediction sequence through a preset recurrent neural network, fusing topological and time sequence data to determine a health score vector, analyzing the matching degree of the health score vector with historical records, and generating a risk traceability warning if the matching degree is lower than a threshold. The method can realize accurate positioning and evaluate the overall health state of a pipeline system.

Provided in the present invention are an automatic color matching configuration method and apparatus suitable for marble. The method comprises: acquiring a to‑be‑repaired-marble image of marble to be repaired, and performing identification to determine a to‑be‑repaired contour in the to‑be‑repaired-marble image; extending outward by a preset distance from the to‑be‑repaired contour, so as to generate a reference contour, wherein the region between the reference contour and the to‑be‑repaired contour is a reference region; using a base coating material to fill a region to be repaired within the to‑be‑repaired contour, so as to form an initial base coating layer; on the basis of the color proportion condition of the reference region, determining a base pixel value, and on the basis of the base pixel value, performing base color matching on the initial base coating layer to obtain a current base coating layer; on the basis of the pattern distribution condition of the reference region, performing regional color matching on the current base coating layer to obtain a repaired region, and determining the marble to be repaired as marble that has been repaired; and acquiring a repaired-marble image of the marble that has been repaired, and on the basis of the repaired-marble image and the to‑be‑repaired-marble image, generating a historical record entry. By means of the present invention, at least the repair effect of marble is improved.

The application provides an ophthalmic surgical instrument cleaning and disinfecting whole-process intelligent monitoring and quality tracing method, relates to the technical field of medical management, and comprises the following steps: acquiring instrument information, establishing feature and quality control element mapping based on a knowledge graph, generating an adaptive quality control strategy according to a pollution degree and historical records, monitoring and checking process consistency in real time, tracing quality problems and intervening in regulation and control when abnormalities are found, and continuously optimizing quality control parameters. The application realizes intelligent monitoring and quality tracing of the ophthalmic surgical instrument cleaning and disinfecting process, and improves the quality control efficiency and safety.

This invention discloses a blockchain-based method and system for tracing cold chain logistics goods, relating to the field of blockchain logistics traceability technology. The method includes activating a unique physical identifier when goods are loaded into a cold chain carrier, collecting initial state data to generate an initialization data packet, uploading it to a decentralized blockchain network for verification, and then encapsulating it as a genesis block of the traceability chain. During transportation, each preset monitoring node simultaneously reads the identifier and collects environmental data through sensing devices, binds them to generate a node traceability record, and uploads it to the blockchain to verify the historical record as a new block. Upon arrival, a final state confirmation is triggered, collecting state images and final environmental data to generate a termination record, which is then uploaded, verified for integrity, and encapsulated as an end block. This method, through strong binding of physical identifiers and data and dynamic blockchain verification links, achieves tamper-proof data storage throughout the entire chain, improving the credibility and data correlation of cold chain goods traceability.

The application provides a control method of a buried vibration detector, belongs to the technical field of vibration detection control, and has a sealed cubic structure and a magnetic keyless design, is waterproof and pressure-resistant, has strong ground burying stability, and has a service life of 0.5 years; time domain-frequency domain joint analysis combined with effective radius calculation can accurately distinguish between personnel, passenger cars and engineering vehicles and reduce misjudgment; a self-adaptive learning formula dynamically corrects a threshold value, adapts to different soil, temperature and humidity environments, and reduces the false report rate; standardized switching on and off and timing data uploading prolong the endurance and meet long-term unattended monitoring; positioning and transmission are stable: Beidou and GPS dual-mode positioning and cellular network positioning are accurate under a ground burying environment, and data transmission is uninterrupted; the background can realize real-time viewing of the state and historical records, and the operation and maintenance efficiency is improved.

The application provides a recommendation method and system for learning a knowledge graph by fusing interactive attention, comprising: obtaining interactive information of a user-item and information of a knowledge graph, constructing an interactive matrix of the user-item according to historical records of the user scoring the item, and constructing the knowledge graph after mapping entities of a knowledge graph dataset and a recommendation dataset; inputting obtained item features and head entity features of the knowledge graph into a multi-task learning shared module and training the knowledge graph module through an alternating training mode, obtaining a scoring function of a knowledge graph triple through a similarity function; training a recommendation module through the alternating training mode based on the multi-task learning shared module, and finally obtaining a final prediction probability of a user participating in a project through a prediction function. The application can fully mine information contained in the knowledge graph module and the recommendation module, effectively alleviate the problem of failing to utilize context information and data sparsity, and thus improve actual recommendation effect.

The application discloses a fluorine oil cleaning method and device for precision electronics, and relates to the field of intelligent cleaning. The method comprises the following steps: collecting target element characteristics to determine target fluorine oil; obtaining first cleaning control data of the target fluorine oil for soaking and cleaning the target precision electronic element; analyzing the first cleaning control data through a soaking and cleaning evaluation model to obtain a first soaking and cleaning cleanliness index as an analog screening constraint; screening historical fluorine oil cleaning records to obtain target historical records; introducing a cleaning fitness function as an optimization evaluation function; and obtaining second cleaning control data from the target historical records as an optimization space to perform ultrasonic cleaning on the target precision electronic element. The method solves the technical problem that the conventional cleaning method for precision electronics cannot completely remove small stains or residues on the surface of precision electronic parts, resulting in poor cleaning effect, and effectively removes dirt on the surface of precision electronics without affecting the performance of the components.

The present application relates to the technical field of medical health management, in particular to a chronic disease patient health management system based on big data, comprising: constructing a full-dimension personal health record containing static and dynamic information. The data analysis module performs abnormal pattern mining on continuous sign data, and generates a trend graph by associating periodic test data with historical records. The data correlation module constructs a risk correlation matrix based on environmental exposure data, which quantifies the contribution of environmental behavior factors to health indicators. The risk modeling module integrates the above information. The prediction and intervention generation module uses a chronic disease progression prediction model to calculate and synchronously output individualized disease risk warning signals and the corresponding phased health intervention programs. The present application realizes the quantitative attribution of health risk factors and dynamic, phased precision health management.

The application relates to the field of garden management and ecological environment monitoring, and discloses a garden vegetation parameter dynamic monitoring system and method, which comprises a data acquisition module, a data fusion module, a three-dimensional modeling module, a point cloud recovery module, a parameter extraction module and a decision output module. The method comprises the following steps: constructing a three-dimensional garden model by fusing and integrating multi-source point clouds and historical growth data, identifying occlusions and reconstructing structures, extracting vegetation parameters, predicting growth trends, and generating visual maintenance suggestions. The application effectively improves the point cloud coverage integrity under the complex spatial structure of the garden, has high fusion registration accuracy, continuous model structure, strong occlusion area completion capability, can accurately extract structural parameters such as the height, crown width and volume of vegetation, realizes trend prediction in combination with historical records, improves the scientific nature, foresight and automation level of maintenance management, and significantly enhances the intelligent capability of garden ecological monitoring.

This application relates to a method, apparatus, and computer equipment for efficiency analysis of a beverage production line. The method includes: acquiring historical data and current production progress information of the beverage production line; identifying the beverage production process and production duration information for each beverage type based on the historical data; identifying the production timeliness impact information of each production process node for each beverage type; and, based on the production timeliness impact information of each production process node for each beverage type, identifying a timeliness impact inference scheme for each beverage type through a production efficiency analysis strategy; generating current timeliness inference information for each beverage type based on the current production progress information; and generating current predicted production timeliness information for each beverage type based on the current timeliness inference information for each beverage type through a timeliness impact inference scheme for each beverage type. This method improves the accuracy of efficiency analysis of beverage production lines.

The present application relates to the technical field of power infrastructure site safety control, and particularly relates to a method for identifying infrastructure site risks, comprising classifying risk operations according to site operation contents to obtain a classification result; calculating a risk event occurrence factor according to the classification result and site factors; calculating a risk event influence factor according to site factors and historical records; obtaining a monitoring report based on the risk event occurrence factor and the risk event influence factor; and monitoring infrastructure site monitoring videos based on the monitoring report. The present application can reduce the professional skill requirements of monitoring personnel by assisting the monitoring personnel in monitoring infrastructure site videos through the monitoring report, and basic skill personnel can complete complex and professional site safety monitoring work, which greatly improves the stability of monitoring compared with random personnel management. The present application solves the problem that the existing infrastructure site monitoring method is prone to monitoring omissions.

This invention relates to a method and system for activating batteries in distribution terminals, belonging to the field of distribution automation technology. The system is deployed at a distribution automation master station and includes modules for activation strategy management, task execution and monitoring, battery health status assessment, historical record query and archiving, and multiple anti-error verification. The method involves remotely configuring and issuing activation tasks through the master station, monitoring the voltage sequence during battery activation in real time, and recording the voltage U1 before activation, U2 after discharge, and U3 after charging. It constructs a multi-source feature system covering voltage timing, inherent battery characteristics, operating environment, and historical performance, and uses a deep learning model for dynamic assessment and anomaly detection of battery health status. After the task is completed, activation records are automatically generated and archived. This invention achieves remote, accurate, and safe activation testing and intelligent operation and maintenance management of massive numbers of distribution terminal batteries, effectively improving the reliability of power distribution networks.

The information processing apparatus of the present invention includes a processor that performs the following processing: determining the timing for adding a transaction to the blockchain based on historical records of transaction fees related to transactions for writing evidence to the blockchain and historical records of transactions for writing evidence to the blockchain.

The application discloses a production method of a forklift mudguard, and comprises the following steps: detecting the thickness of incoming flat plates to obtain actual thickness information; positioning and centering the incoming flat plates after the thickness detection, and then sending the flat plates into a molding station to determine the first molding parameters according to the actual thickness information and historical molding parameters in a molding parameter database and to perform the first molding; carrying the mudguard semi-finished product to a shape detection station, performing preliminary detection by using a non-contact visual detection unit, and performing re-detection by using a contact detection unit when the preliminary detection is unqualified; when both the preliminary detection and the re-detection are unqualified, determining a compensation area, a compensation quantity and re-molding parameters according to the thickness detection result, feature point deviation information and historical records in the molding parameter database, performing re-molding after placing a gasket in the corresponding area of a concave cavity of a molding die, and writing the molding parameters, the detection result and the compensation result into the molding parameter database. The application can improve the forming quality stability of the mudguard.

This application provides an interactive method and system for detecting large leaks in energy storage air conditioners, relating to the field of energy storage air conditioner technology. This method significantly improves the convenience and consistency of large leak detection by integrating a full-process interactive interface that includes workpiece model selection, intelligent parameter configuration, one-click start, real-time multi-dimensional monitoring, and result visualization and backtracking. Users can quickly select the model and automatically load suitable flexible pressurization rules and gradient pressure relief programs, avoiding manual missetting. During the detection process, the current stage, pressure value, pressure-time curve, remaining pressure holding time, and acoustic emission status are dynamically displayed, allowing real-time monitoring of pressure resistance and structural safety, preventing damage to the workpiece structure during large leak detection. After completion, the judgment result is automatically displayed, linked to historical records, pressure decay rate, and alarm logs. It supports process curve playback and one-click generation of standardized test reports, greatly improving efficiency, traceability, and quality control.

The application relates to the technical field of data processing, and discloses an operation data real-time monitoring and early warning method based on stream computing, which comprises the following steps: collecting physical operation indexes to determine a current operation state, encapsulating the operation state and control permission into a state token, and delivering the state token to a downstream node; when a time window reaches a boundary, verifying token consistency to control window closure; isolating and storing normal and delayed arrival data, and respectively aggregating the data into summaries; extracting the summaries to perform non-recalculation algebraic synthesis to generate index results, and performing coverage update on historical records; routing the results to a tree-shaped baseline according to token permission to perform update or isolated deliberation to output early warning results. The application decouples the strong dependence of a time window on a delayed data stream, avoids memory expansion caused by full recalculation through memory isolation aggregation, and effectively distinguishes system fluctuation and business migration based on tree-shaped baseline evolution, thereby improving the accuracy of early warning results.

The application relates to a smart park security management method, system, device and medium, and belongs to the technical field of smart parks, which comprises the following steps: receiving an access reservation form, identifying the unique identifier of a visitor and a reservation event, and querying historical records in a visit event library according to the unique identifier to calculate initial trust points. Based on the points and the reservation event, a dynamic authorization seed is created, and an access link containing the seed is sent to the visitor end. After entering the park, the initial dynamic access corridor and the permission accompanying unit are generated by using the dynamic authorization seed to guide the visitor to move. When the visitor approaches the target site, the first sub-permission is granted in the adjacent area to allow entry; after entering the target site, the second sub-permission is granted in combination with the historical visit information of the target site and the visitor's own record. When it is detected that the visitor is leaving, the permission recovery instruction is broadcasted to all network edge nodes, the visitor portrait is updated, and the local cache is emptied; the visitor experience is improved, and the security protection capability of the park is strengthened.

The application discloses a wide-area networking telecommunication value-added service online test method, and particularly relates to the technical field of telecommunication network and data processing. A unique uplink session identifier is generated by combining and encoding the uplink test request sent by a user terminal, and is associated with the downlink service flow serial identifier returned by a service provider to form a closed-loop identifier pair. Further, a state space mapping is constructed based on a time sequence, path consistency of the closed-loop identifier pair is determined, and constraint screening is performed before sending. Downlink message sending is only performed when the unique mapping path is met and the case is not covered by historical records. Meanwhile, a state convergence mark is applied after sending, and repeated sending is blocked through trajectory backtracking when abnormal retry occurs. The application realizes unique control of the message sending path by constructing a time evolution trajectory and a closed-loop constraint relationship, effectively avoids repeated sending and message storm problems, and improves the stability and reliability of the telecommunication network test process.

This invention discloses a closed-loop management method driven by a holographic ledger for supplementary medical reimbursement in enterprises, comprising: initializing holographic ledger records containing a finite state machine instance and a hash chain storage area; performing hash verification before each step starts, and starting the step after passing the verification, outputting the hash and writing it into the hash chain to form an immutable evidence chain, which is automatically migrated by the state machine; extracting the fiber texture of the invoice and the microscopic imprint features of the papermaking equipment and combining them into a joint physical fingerprint, which is bound to the business data hash value via HMAC-SHA256 to generate a two-layer fusion verification vector; comparing this vector with historical records in multiple dimensions and verifying the integrity of the hash chain, distinguishing the anomaly type and triggering differentiated processing; intercepting and triggering review when an anomaly occurs, and adaptively adjusting the judgment threshold based on the review result using an exponentially weighted moving average method to form a ledger-driven closed-loop traceability chain; this invention realizes ledger active driving, data hash chain closed-loop locking, two-layer traceability of invoice physical features, and adaptive optimization of detection parameters.

This invention discloses a large-scale grounding grid corrosion status assessment system based on big data analysis, comprising: a data acquisition module for collecting node resistance, potential, conductivity, humidity, and temperature, and recording time and node data; a data processing module for denoising, normalizing, and correcting data to generate a structured data matrix; a feature extraction module for extracting corrosion feature vectors based on historical records; a corrosion assessment module for probabilistic model inference and scoring to generate corrosion levels, risk matrices, and health trends; a corrosion distribution module for interpolation mapping to generate a full-network corrosion distribution map and marking high-risk nodes; a trend prediction module for simulating evolution to generate future corrosion level change curves and high-risk rankings; and a report generation module for generating a status assessment report. This invention utilizes big data analysis technology to achieve accurate corrosion assessment, risk visualization, and health trend prediction for grounding grids, improving maintenance decision-making efficiency.

We provide the system. [Solution] A means of automatically classifying uploaded information based on its attributes, A means of converting classified information into an integrated format, Means of obtaining additional information on relevant information and historical background from external sources, A means of generating digital records that take into account the user's characteristics and history, A means of providing the generated digital record to the user's device in a viewable format, A method for adding narration and music to digital content using a generative AI model to create visual deliverables based on a storyline, A system that includes this.