45results about How to "Avoid one-sidedness" patented technology

The invention belongs to the crossing field of network space security, software engineering and artificial intelligence, and discloses a dynamic and static cooperative vulnerability full-link intelligent analysis and verification method based on a large language model and an MCP protocol, and the method comprises the steps: S1, task initialization and context construction; s2, target code deep analysis and static taint preanalysis are carried out; s3, carrying out Fuzzing Harness directional generation and iterative optimization on the basis of the stain paths; s4, performing dynamic and static collaborative sandbox execution and dynamic stain tracking; and S5, vulnerability accessibility judgment and report output of multi-source data fusion are carried out. According to the method, a dynamic and static combination mechanism is adopted, vulnerability analysis and verification can be automatically completed for software target codes, and accurate technical support is provided for vulnerability risk grading and repairing priority ranking.

The application provides a multi-dimension evaluation method for an interference scene, which solves the problems of evaluation hysteresis, improves the consistency of evaluation, solves the single dimension of evaluation and the lack of consideration of terrain in the evaluation of the interference scene; the position accessibility analysis of terrain perception of a propagation path between a signal simulation device and a target device is carried out based on a digital elevation model; the device behavior compliance analysis is carried out in four dimensions of time domain, space domain, frequency domain and energy domain; if there is a moving route, the route coverage and signal continuity analysis are carried out in combination with the analysis results of the former two; finally, the analysis results of the three dimensions are weighted and fused to calculate the scene comprehensive effectiveness score and map it to high, medium and low three levels of confidence. Through the construction of the multi-dimension collaborative pre-evaluation system, the scientific and quantitative pre-evaluation of the training scene planning scheme is realized, the planning quality and efficiency are effectively improved, and the risk of waste of training resources is reduced.

This invention discloses an AI-based physical education exam scoring method, belonging to the field of exam scoring methods, including the following steps: (1) activating the cameras deployed in the exam room to collect motion images and facial expression images of the examinee during pull-ups; (2) analyzing the collected facial expression images using AI image recognition technology to divide the exam process into three stages; (3) for each stage, analyzing the examinee's motion images using AI technology to determine whether each pull-up motion is a qualified motion; (4) counting the number of qualified motions in each stage and scoring them separately, adding the scores of the three stages to obtain the examinee's final exam score. This invention can divide the exam into three stages based on facial expression recognition, perform differentiated analysis on the motion characteristics of each stage, better fit the examinee's physical fitness change patterns, and make the evaluation results more targeted.

The application discloses a kind of thermal power plant rotary air preheater comprehensive health evaluation method and system, determine multiple characteristic parameters, and based on the weight coefficient and deviation degree of each characteristic parameter, comprehensive calculation is carried out, the one-sidedness caused by the evaluation of only single parameter is avoided, and the evaluation result can more truly reflect the overall operation condition of equipment, the deviation degree range of each characteristic parameter used for air preheater comprehensive health evaluation is given in calculation, and the evaluation result of different degrees of influence on comprehensive health index is obtained in later period, the method provides definite maintenance basis for field operation, and ensures the stable operation of thermal power plant rotary air preheater.

This invention provides a method, apparatus, electronic device, and storage medium for identifying critical nodes. The method includes: determining multiple indicator values ​​for any node based on multiple indicators, whereby the multiple indicators are used to evaluate the importance of the node; determining the comprehensive weight corresponding to any indicator using the analytic hierarchy process (AHP) and entropy weight method; determining the node's importance ranking value based on the multiple indicator values ​​and the comprehensive weights corresponding to the multiple indicators for any node; and identifying critical nodes based on the node importance ranking values ​​of all nodes. This invention solves the problem of the one-sidedness of existing critical node identification methods in related technologies.

The application discloses a detection method of Baizhu San standard decoction fingerprint combined with liquid chromatography-mass spectrometry, the fingerprint and application thereof, and belongs to the field of traditional Chinese medicine quality standard research and application. Test sample solution and single control sample solution are injected into a high performance liquid chromatograph to obtain respective chromatograms; mass spectrometry analysis is conducted on the test sample solution to obtain mass spectrometry results; common peaks existing in the chromatogram of the test sample solution are taken as common peaks, chemical components in the Baizhu San standard decoction are identified in combination with the chromatogram of the single control sample solution and the mass spectrometry results of the test sample solution, and the Baizhu San standard decoction fingerprint is obtained. The fingerprint is constructed through liquid chromatography-mass spectrometry, 10 intersecting components are identified in combination with the mass spectrometry information of the control sample, so that the quality control of the Baizhu San standard decoction is realized, the method is simple, easy to operate, high in precision, good in stability and reproducibility, and can effectively solve the technical problem that the quality of the Baizhu San cannot be effectively evaluated.

The application relates to the technical field of detection of electrified railway contact network systems, and discloses a contact network system fluorescent fingerprint intelligent analysis system, which comprises a visual unit, an emitting unit, a deflection unit, a receiving unit, a detection unit and a main control unit. The visual unit calculates relative motion parameters of insulators, drives the deflection unit to perform reverse compensation motion, so that a laser landing point remains stationary relative to a target surface within an integration time. The detection unit respectively collects parallel and vertical polarization components of Rayleigh scattering light and Stokes luminescence after spectral separation. The main control unit calculates a surface roughness factor by using the Rayleigh scattering component, carries out numerical correction on a polarization anisotropy parameter of the Stokes luminescence, eliminates the influence of geometric depolarization, and extracts fluorescent lifetime and rotation-related time characteristics. The application solves the fluorescent detection distortion problem caused by rough surfaces in a dynamic environment, and realizes multi-dimensional diagnosis of the contamination type and the substrate aging degree of the insulator surface.

This invention proposes an intelligent matching and allocation method and device for experts and projects. The method includes: constructing a multi-dimensional fusion matching model based on acquired expert and project information. This model calculates a comprehensive matching score between experts and corresponding projects by weighted fusion of sub-scores based on expert professional matching degree, experience fit, workload balance, and geographical distribution balance; selecting a matching algorithm based on the number of experts and projects to be allocated; using a first matching algorithm when the problem size is no greater than a preset threshold; and using a second matching algorithm when the problem size is greater than the preset threshold; and generating the optimal matching scheme between experts and projects based on the comprehensive matching score using the selected matching algorithm. Based on this method, this invention also proposes an intelligent matching and allocation device for experts and projects. This invention achieves more accurate quantitative matching by constructing a comprehensive evaluation model integrating four dimensions: professional expertise, experience, workload, and geographical distribution.

This invention relates to the field of data retrieval technology, specifically disclosing a database-based method for rapid retrieval of skills learning data, comprising the following steps: S1: Preset a retrieval period, statistically analyze the types, occurrences, and frequencies of retrieval fields within the period, and stop if the threshold is not met; S2: Construct binary retrieval field combinations, calculate the frequency and correlation coefficient of each combination field; S3: Single-field retrieval matches initial courses, calculates popularity based on the number of enrollees and collections, and sorts them; S4: Divide primary and secondary fields to correct popularity, sort and filter popular courses, and establish a connection between combinations and courses; S5: Prioritize displaying related popular courses, continuously update the period, and repeat the process after decomposing multi-field combinations. This method can improve retrieval accuracy and efficiency, ensure course timeliness and recommendation quality, adapt to the needs of skills training platforms, optimize resource allocation, and enhance the platform's core competitiveness.

This invention relates to a method and system for constructing a database of wild rice introduction lines. The method includes: acquiring raw genotype data, sample metadata, and phenotypic data of individual samples from multiple wild rice introduction line populations, where the sample metadata includes a sample number; parsing and identifying the raw genotype data to determine the fragment location, fragment type, and fragment length of the wild rice introduction fragment, thus obtaining the corresponding genotype data; and, based on the sample number, associating and integrating the genotype data, sample metadata, and phenotypic data to generate a structured dataset. This structured dataset is then used to construct a database corresponding to multiple wild rice introduction line populations, improving the integration and correlation of wild rice introduction line data, promoting the collaborative utilization of genetic resources, facilitating the sharing of genetic resources among wild rice introduction line populations, and enhancing the interoperability and value of scientific research resources.

This invention discloses a quantitative assessment and adaptive intervention system and method for fluidized tissue, belonging to the fields of enterprise management informatization and artificial intelligence technology. The system includes: a data acquisition module for acquiring role change logs, reporting relationship change logs, and process instance generation logs; a DRSF calculation unit for calculating the dynamic role switching frequency; an RSI calculation unit for calculating the reporting relationship stability index; a PGA calculation unit for calculating the process generation autonomy; a comprehensive index generation module for standardizing and weighting DRSF, RSI, and PGA to generate a comprehensive fluidized tissue index (LOI); and an intervention recommendation module for automatically generating organizational intervention suggestions when the indicators exceed thresholds. This invention proposes for the first time three quantifiable organizational fluidization assessment indicators: DRSF, RSI, and PGA, achieving multi-dimensional comprehensive diagnosis of organizational fluidity and automatically triggering interventions based on thresholds to form a closed-loop optimization. This invention can be embedded into existing enterprise management systems, providing a quantitative tool for digital transformation.

The application discloses a kind of multi-level man-machine collaborative data labeling method and system based on task ambiguity evaluation, first constructs and trains ambiguity prediction model, utilizes lightweight ambiguity prediction model, predicts the cognitive ambiguity score and logic ambiguity score of each data instance;Four-stage labeling resource pool containing low-performance large language model, high-performance large language model, ordinary crowd sourcing labeler and expert labeler is constructed;According to the predicted two-dimensional ambiguity score, the data instance is automatically routed to the optimal labeling resource by dynamic scheduling strategy, for the task with high cognitive ambiguity, the upgrading mechanism combining crowd sourcing voting and expert arbitration is used, and the final labeled data set is output.The application can intelligently match labeling cost and ability according to the intrinsic properties of the task, significantly reduce the labeling cost and improve the labeling efficiency under the premise of ensuring the data labeling quality, solve the problem of high cost of traditional crowd sourcing and unstable quality of single model labeling.

This invention relates to the field of photovoltaic power generation fault diagnosis technology, and in particular to a photovoltaic array fault diagnosis system and method based on artificial intelligence. By encrypting and preprocessing multi-source data, a multimodal dataset is constructed, providing a comprehensive and collaborative data foundation for subsequent analysis. The collaborative diagnosis model can analyze the battery and inverter status in parallel. By combining circuit equivalent models, spatial adjacency relationships, and theoretical power models for calculation, the diagnosis results have physical interpretability. A physical consistency verification rule based on power flow analysis is introduced to cross-validate and logically fuse the preliminary diagnosis results, generating reliable comprehensive fault diagnosis results. This approach solves the technical problem in existing technologies that focus on independent analysis of single components such as photovoltaic cells or inverters, lacking effective fusion and collaborative utilization of multi-source heterogeneous data, which limits the accuracy of diagnosis results.

This invention discloses an automatic detection method, device, equipment, and medium for vehicle parking status at intersections. The method includes: when a vehicle is detected entering the intersection, acquiring trajectory point data consisting of multiple continuous trajectory points, including the current trajectory point; collaboratively determining whether the vehicle is parked based on the velocity, acceleration, and jerk of each trajectory point in the event window trajectory point data; and determining the parking status based on the parking duration when the vehicle is determined to be parked and its travel direction is consistent with the main traffic direction corresponding to the intersection. This invention accurately distinguishes between effective parking and low-speed creep scenarios through multi-point collaborative analysis, and eliminates interference by combining directional consistency verification. Without relying on additional hardware and high-precision maps, it achieves low-cost, high-precision, low-interference, and wide-coverage automatic detection and hierarchical early warning of parking behavior at intersections.

The application belongs to the cross field of network space security, software engineering and artificial intelligence, and discloses a kind of dynamic and static cooperative type vulnerability full-link intelligent analysis and verification method based on large language model and MCP protocol, comprising: S1: task initialization and context construction;S2: target code depth analysis and static stain pre-analysis;S3: Fuzzing Harness directional generation and iterative optimization based on stain path;S4: dynamic and static cooperative sandbox execution and dynamic stain tracking;S5: vulnerability accessibility determination and report output of multi-source data fusion.The application method adopts dynamic and static combination mechanism, and can automatically complete vulnerability analysis and verification for software target code, providing accurate technical support for vulnerability risk grading and repair priority sorting.

The application provides a water supply pipe operation safety monitoring method, and belongs to the technical field of automatic monitoring. The method comprises the following steps: acquiring geological micro-motion data, pipe deformation data, interface state data and water power monitoring data of each monitoring section in a current detection period; determining current geological micro-motion abnormality, current pipe deformation abnormality, current interface state abnormality and current water power parameter abnormality of each monitoring section; for each monitoring section, calculating a correlation coefficient between a historical geological micro-motion abnormality sequence and a historical pipe deformation abnormality sequence of the monitoring section; if the correlation coefficient is greater than a preset correlation threshold, determining respective weights of multi-dimensional abnormality degrees of the monitoring section based on a first weight distribution strategy; and performing weighted summation on the multi-dimensional abnormality degrees of each monitoring section to determine a water supply pipe operation safety monitoring result of each monitoring section. The application can realize early warning of water supply pipe operation safety monitoring.

This invention relates to a method for detecting characteristic chromatograms of anti-inflammatory granules or their intermediate extracts, and its application. The anti-inflammatory granules or their intermediate extracts are prepared from the following medicinal ingredients: Astragalus membranaceus, Panax notoginseng, Salvia miltiorrhiza, Paeonia lactiflora, Stephania tetrandra, Alisma plantago-aquatica, Coix lacryma-jobi, Poria cocos, and Achyranthes bidentata. The detection method is high-performance liquid chromatography (HPLC). The HPLC conditions are: an octadecylsilane-bonded silica gel column, acetonitrile as mobile phase A, and phosphoric acid aqueous solution as mobile phase B, with gradient elution. The method of this invention can obtain characteristic chromatograms with high information content and high peak response values. This method can effectively control the key quality attributes of anti-inflammatory granules and is conducive to industrial promotion, which is of great significance for the quality control standards of anti-inflammatory granules.

This disclosure relates to the field of power system technology, and discloses a method, apparatus, equipment, and storage medium for medium- and long-term power planning based on the characteristics of next-generation coal-fired power plants. The method involves constructing a first multi-dimensional operational constraint for next-generation coal-fired power units based on multi-dimensional characteristics, including clean energy reduction, safety, efficient regulation, and intelligent operation. A second multi-dimensional operational constraint is constructed based on the requirements for multi-source coordinated operation. A target constraint system for next-generation coal-fired power units is then constructed based on the first, second, and comprehensive cost constraints. The initial installed capacity scheme is iteratively optimized using a target time-series production model combined with the target constraint system to obtain the target installed capacity scheme. Through the first multi-dimensional operational constraint, the four core characteristics of clean energy reduction, safety, efficient regulation, and intelligent operation are accurately covered, effectively solving the problem of inaccurate characterization of coal-fired power plants.

This invention provides an interactive sports training assessment method and system, belonging to the field of sports training assessment technology. The method involves: distributing an assessment item set in a virtual training assessment scenario; sorting the items according to the trainee's exercise habits and psychological state for each assessment item; sequentially displaying the items and capturing training behavior posture sets; globally comparing these with a standard posture set to construct joint point abnormal posture vectors; and combining joint point behavior trajectories with standard trajectories to construct point abnormal vectors; combining and analyzing these results to obtain single-item assessment results; and finally, processing all results and sending them to the assessment terminal. This invention achieves standardized quantification of assessments, improves the objectivity and accuracy of assessments, and provides a scientific reference for sports training.

The application provides a large model evaluation method and device based on multi-end interaction verification, equipment and medium, belonging to the technical field of large model evaluation, the method comprises the following steps: inputting a plurality of test instructions in a target test instruction sequence into a to-be-tested large model according to a preset order, and determining an implicit risk metric when the state of the to-be-tested large model changes; based on a first evaluation end and a second evaluation end, the answers output by the to-be-tested large model when the state changes are evaluated to obtain a first evaluation result and a second evaluation result; based on the first evaluation result and the second evaluation result, the global cognitive energy is determined; according to the implicit risk metric, a convergence threshold is determined; the evaluation results of the first evaluation end and the second evaluation end are exchanged, and the global cognitive energy is recalculated until the global cognitive energy is not greater than the convergence threshold, and based on the first evaluation result and the second evaluation result determined last, the evaluation result of the to-be-tested large model is determined. The application can improve the accuracy of the large model evaluation result.

This invention relates to a hyperspectral band selection method based on spectral-spatial hypergraph regularized sparse self-representation. To address the insufficient utilization of band adjacency relationships in traditional sparse self-representation models, this method first integrates spectral similarity and spatial proximity to design a comprehensive index for evaluating band correlation. It explores and evaluates adjacency relationships between bands from multiple perspectives, constructing a hypergraph to generate a more complete inter-spectral local structure. Second, based on the aforementioned local band constraints, it supplements this with global band characteristics to jointly guide the optimization process of the sparse self-representation band selection model, obtaining the optimal low-dimensional representation of high-dimensional data and achieving band selection. This method overcomes the limitations of using a single similarity metric for decision-making and fully explores the multi-faceted adjacency relationships between bands, effectively reducing band redundancy, improving the quality of band subsets, and contributing to improved analytical accuracy in subsequent tasks.

This invention discloses a smart classroom control method and system based on multimodal cognitive state assessment, relating to the field of teaching technology. The key technical points include the following steps: collecting multi-dimensional perception data of the smart classroom; wherein the multi-dimensional perception data includes student cognitive behavior data and teaching process state data; performing feature analysis on student cognitive behavior data to obtain cognitive features; continuously tracking and analyzing student cognitive feedback data to obtain individual cognitive fit and group cognitive synergy; verifying the cognitive synergy recovery state of the smart classroom based on individual cognitive fit and group cognitive synergy; and judging the cognitive synergy recovery state to determine whether classroom control is needed. The effect is to improve the utilization efficiency of teaching resources and reduce the consumption of ineffective teaching.

The present application relates to a method for optimizing parameters of a marine closed cooling water system based on multi-objective decision-making. The method comprises the following steps: obtaining the attribute parameters of the cooling medium and the heat exchange equipment, grasping the system parameters of the cooled medium, setting the boundary conditions of the primary and secondary heat exchange temperature differences, and inputting these parameters into an optimization model of the closed cooling water system; generating all parameter combination schemes that meet the constraint conditions through the exhaustion method; further classifying and descendingly sorting the schemes according to the same primary heat exchange flow, respectively selecting the primary and secondary heat exchange flows and the total heat exchange area as different decision-making objectives for hierarchical optimization and screening to obtain an optimized scheme of multi-parameter combination; further setting the primary heat exchange flow value percentage increase ⊿Q f % and the secondary heat exchange flow value percentage increase ⊿Q s % or the primary and secondary heat exchange temperature differences to obtain an optimal scheme of multi-parameter combination, so as to realize the dual objectives of cost reduction and energy saving of the marine closed cooling water system.

This invention discloses a computing power optimization method based on an industrial control gateway, characterized by the following steps: collecting computing power index data of each node through the industrial control gateway and calculating the comprehensive computing power score of each node; setting the number of grids and setting the upper limit of the total comprehensive computing power score for each grid; dividing all nodes into corresponding grids using the K-means algorithm; calculating the comprehensive performance evaluation value of each grid based on the computing task completion time, resource utilization, and communication latency; allocating computing tasks to the grid with the lowest comprehensive performance evaluation value; and executing computing tasks through the nodes in the grid. This invention, through grid partitioning, achieves refined management of computing resources and a high degree of matching between computing task execution and performance, improving production efficiency and reducing operation and maintenance costs.

The invention discloses a learning rejection behavior evaluation method and device, electronic equipment and a readable storage medium. The method comprises the steps of obtaining at least two course videos corresponding to a to-be-evaluated object in a preset evaluation interval, and inputting the at least two course videos into a target evaluation model; for any course video in the at least two course videos, acquiring a multi-modal feature sequence corresponding to the to-be-evaluated object; performing state analysis on the multi-modal feature codes corresponding to the multi-modal feature sequence through expert networks of at least two dimensions in the target evaluation model to obtain learning state features of at least two dimensions; and based on the learning state features corresponding to the at least two dimensions corresponding to the at least two course videos, obtaining a learning state score corresponding to the to-be-evaluated object output by the target evaluation model. Therefore, the learning state score is obtained based on the multi-course video and the multi-dimensional learning state features, so that the evaluation result is more practical, and the evaluation accuracy and interpretability are improved.

The invention discloses a land resource asset servicing time sequence simulation method, which comprises the following steps: acquiring construction map spot data of a target area in historical years, and performing spatial rasterization processing to obtain a grid map layer in a map spot state in multiple years; calculating a current land resource asset servicing resistance comprehensive value of each grid layer based on a preset servicing resistance evaluation system; constructing a space-time probability prediction model, and performing parameter fitting by using map spot data for construction in historical years; calculating the prediction probability of each grid layer in the target year based on the fitted space-time probability prediction model; the servicing resistance comprehensive value and the prediction probability of each grid layer are synthesized, and a servicing implementation potential value of each grid layer is calculated; and based on the servicing implementation potential value, generating a suggested scheme for guiding a land resource asset servicing implementation time sequence. According to the method, the limitation of traditional static evaluation is overcome, continuous simulation of a servicing time sequence is realized, and a decision basis is provided for medium-and-long-term land servicing planning.

The application discloses a kind of network type converter and electric heat cold energy storage system collaborative optimization control method, contain steps as follows: construct "network type converter-electric heat cold energy storage-flexible load" multi-objective optimization model;Establish the collaborative constraint of network type converter and energy storage system;Establish demand response and network state linkage mechanism;Solve the multi-objective optimization problem by NNC algorithm and combine TOPSIS method to filter optimal operation scheme;According to optimal operation scheme, dynamically adjust the virtual inertia and droop coefficient of network type converter, synchronously dispatch electric energy storage charge-discharge power and cold energy storage and / or heat energy storage electric drive equipment operating state.The method can quickly and accurately suppress new energy output fluctuation and load mutation, strictly constrain system voltage deviation and frequency deviation within a more optimal operating range, fundamentally enhancing the transient stability and dynamic power quality of the grid with high proportion of new energy access.

The application discloses a kind of based on load prediction's air conditioner wind system overhaul time judgment and control method, this method includes: obtaining workshop air volume and temperature and humidity upper limit value, and calculating enthalpy upper limit value;Obtain the cooling capacity required for maintenance matching preset maintenance period, and according to the cooling capacity required for maintenance and workshop air volume, calculate target enthalpy difference;According to target enthalpy difference and enthalpy upper limit value, calculate target air enthalpy;Obtain current temperature and current humidity in workshop, calculate current air enthalpy;Target air enthalpy is compared with current air enthalpy, and determine the maintenance scheme matched with comparison result, avoid the one-sidedness of single temperature and humidity parameter control, can more comprehensive and accurate reflect indoor air energy state, provide basis for environmental protection during maintenance, avoid environmental over-standard risk, guarantee the stability of environment during maintenance, help fast recovery production after maintenance, improve overall production efficiency, automation and intelligent level of maintenance judgment and control.

The application discloses a multi-modal emotion recognition and intelligent guidance device for English learning, comprising a learning terminal, a somatosensory data collector and a central processor. The learning terminal is used for presenting learning content and recording user learning interaction logs. The somatosensory data collector is used for collecting user video stream data and stress distribution data. The central processor comprises a multi-modal feature extraction module, a risk assessment module, a guidance decision module and a content generation module. The device extracts negative interaction behavior features from the logs, extracts posture withdrawal features from the video stream and extracts stress deviation features from the stress data. The user's learned helplessness risk level is obtained through a psychological risk assessment model, a target guidance strategy is matched according to the risk level, and guidance content for cognitive reconstruction is generated and embedded in the learning content. The device can more accurately identify deep psychological risks and provide targeted intervention.

The present application relates to the field of geological disaster monitoring and warning and geotechnical engineering informatization, and discloses a kind of satellite InSAR and ground displacement joint restraint's slope digital twinborn self-update and early warning method, solve the existing slope monitoring technology There are problems such as difficult multi-source data fusion, stability analysis cannot dynamically update parameters and sliding surface geometry, lack of digital twinborn model self-update capability and single early warning index.The present application fuses satellite InSAR surface deformation, ground GNSS point deformation, deep profile deformation data under unified space-time and coordinate datum, realizes the real-time self-update of model by constructing twinborn model augmented state containing geotechnical parameters and sliding surface geometric parameters, combined with hierarchical consistency constraint objective function, then fuses static stability index of limit equilibrium method and dynamic deformation index of proxy model, forms comprehensive hierarchical early warning system considering static stability and dynamic deformation characteristics of slope.