46results about How to "Convenient verification" patented technology

The invention provides a method for regulating and controlling a hydrodynamic balance valve with a real-time load feedback function, and the method comprises the steps: collecting the strain, water level, gas, vibration and motor current data of the balance valve in real time, constructing and utilizing a comprehensive load balance model, and calculating the effective safety torque of the balance valve in real time at an edge calculation layer; a mechanical wear degradation factor is calculated based on the action history and the current variance of the locking mechanism, and the instantaneous instability risk probability is calculated in combination with the effective safety torque and the current locking torque; according to the instantaneous instability risk probability, an output mode of a locking mechanism is dynamically adjusted to execute a graded locking action; and periodically calculating a full-life-cycle health degree index, and automatically generating a maintenance or replacement work order when the full-life-cycle health degree index is lower than a preset threshold value. According to the invention, the conversion from passive alarm to active defense is realized, and the safety and operation and maintenance efficiency of the urban balance valve in rainstorm, heavy load and corrosion environments are obviously improved.

The invention provides an XR glasses total factor fusion simulation verification platform building method, and belongs to the technical field of airborne simulation cockpit display, and the method comprises the steps: building a simulation environment sensor system working model, and obtaining sensor system model data; dividing working modes of the XR glasses according to the flight scene; constructing a simulation environment man-machine interaction and control model; based on sensor system model data and a simulation environment man-machine interaction and control model, a simulation verification environment corresponding to all XR glasses working modes is built, and an XR glasses total factor fusion simulation verification platform is built. A verification platform built by the method realizes fusion display function simulation of airborne sensor data in the XR glasses, and a total factor simulation model of the XR glasses is built; the real flight and man-machine interaction process of the fighter can be simulated, and the real degree of the simulation verification process is improved; the simulation cost can be reduced, and the pre-research function can be conveniently verified.

This application relates to a scheduling method, apparatus, computer equipment, storage medium, and computer program product for power operation tickets. The method includes: dividing the fields to be verified in the power operation ticket into regions based on the correlation characteristics between them and their location characteristics; verifying the fields in each region to obtain a verification result for each region; weighting the verification values ​​of each result according to the type of the result and the order of the regions to obtain a weighted verification result for the power operation ticket; and distributing power operation tickets according to the operation objects matched by the weighted verification values ​​in the weighted verification result. This method eliminates the need for manual verification of the fields to be verified, reducing the verification time for power operation tickets and thus improving the efficiency of power system maintenance.

This invention relates to the field of roadside perception technology, specifically disclosing a multimodal roadside safety perception and linkage early warning method and system based on deep learning. The method includes: collecting target information and verifying first identification signals with the same target number to identify error information; predicting the simulated driving path of the vehicle and calculating a risk assessment value; marking abnormal driving points by determining whether the simulated driving point has contact with the target object; calculating the risk assessment value based on the distribution of abnormal driving points; and after identifying that the target vehicle is in a risky state, extracting a second identification signal composed of a single source to determine the detailed risk level of the risk state. This invention transforms the differences between devices, which are considered interference in traditional perception systems, into a core basis for proactively predicting and quantifying potential risks. It also provides differentiated responses based on the urgency and severity of the risk, reducing unnecessary interference to the driver while ensuring safety.

The application discloses a kind of multi-micronet robust game optimization scheduling method and system based on dynamic auction official algorithm, and relates to energy system scheduling and optimization technical field.The method constructs system physical model and double-layer robust optimization model based on Stackelberg master-slave game, upper layer maximizes system operator's profit to formulate price signal, lower layer maximizes the worst scenario income of multi-micronet alliance to optimize resource scheduling, combined with multiple constraint conditions, Stackelberg equilibrium is solved iteratively using dynamic auction official algorithm.The application converges to global optimal solution quickly through three-dimensional hybrid driving price updating mechanism, realizes system economic benefit maximization, operation robust and reliable, and has good explainability and practical application value.

The application provides a concurrent vulnerability verification method and device, electronic equipment and readable storage medium, applied to the computer kernel security field, including: obtaining a first interleaved sequence in the computer kernel; the first interleaved sequence includes: a plurality of memory operation instructions; the plurality of memory operation instructions executed according to a target condition are used to trigger a concurrent vulnerability; adding a breakpoint before each memory operation instruction in the first interleaved sequence to obtain a second interleaved sequence and execute; the breakpoint is used to make the memory operation instruction after the breakpoint enter a waiting state; based on the memory operation instruction entering the waiting state and the target condition, the trigger information of the concurrent vulnerability is output. The embodiment adjusts the execution order of the interleaved sequence using the breakpoint, so that the execution process meets the target condition, and solves the problems of expected interleaved sequence execution interference and low reproduction efficiency.

This invention provides a method for detecting AAV antibody titers, belonging to the field of biomedical technology, comprising: S1 preparing serum-free AAV vectors with different MOI values; preparing a mixture containing different volumes of test serum samples and AAV vectors with known MOI values ​​for co-incubation; S2: adding plasmids containing the CRISPR-Cas9 gene editing system to electroporation buffer, performing electroporation on a known number of cells, adding the serum-free AAV vectors and mixture from step S1 to the electroporated cells respectively, and detecting the expression efficiency of the reporter gene after electroporation; S3: calculating the AAV antibody titer in the test serum sample based on the detection results. The main advantage of this invention is that it can display AAV antibody titers digitally and quantitatively, facilitating understanding and communication, and obtaining stable and reliable results using different cell lines and different AAV transduction doses. This method is easy to standardize and validate, saving time, effort, and detection costs compared to traditional methods, and directly reflects antibody neutralizing activity.

The application provides a kind of escalator handrail belt speed measuring device, speed measuring device is installed on handrail belt, speed measuring device includes main unit, clamping component, speed measuring component and control component, control component is used to control the operation of speed measuring device, main unit has drive assembly, drive assembly has transmission rod and support rod, clamping component has two sets of clamping pieces, transmission rod and support rod are connected with two sets of clamping pieces, transmission rod drives two sets of clamping pieces to realize split and combined motion, clamping piece is clamped on handrail belt, speed measuring component is installed at the lower end of clamping piece, speed measuring component has support wheel and speed measuring wheel, support wheel and speed measuring wheel contact with handrail belt mounting frame, speed measuring wheel is used to measure the running speed of handrail belt;The application can realize the direct measurement of handrail belt speed, obtain continuous data of handrail belt operation, obtain the state of each point of handrail belt operation in time, which is beneficial to accurately diagnose the running state of handrail belt, and the device has the characteristics of convenient operation and high efficiency.

This invention discloses a device and method for simulating the effects of salinity stress during freeze-thaw cycles on the rhizome germination of emergent plants, belonging to the field of emergent plant germination experiments in cold and arid regions. The device includes an outdoor main pool and a laboratory auxiliary pool, connected by a closed channel with double gates. The bottom of the main and auxiliary pools is equipped with sliding tracks and transfer channels. Within the transfer channels, a translation screw, in conjunction with an electromagnet, drives the base frame to move without breaking ice. The main pool is equipped with freeze-thaw, salinity, and nutrient regulation modules. The method uses an L18 (3²×6¹) orthogonal array to design experimental combinations of freeze-thaw patterns, salinity, and nutrients. The base frame is transferred to the auxiliary pool without breaking ice, and stratified morphological and physiological indicators are measured simultaneously. Data are harvested at the end of the experiment, and variance analysis is performed. This invention achieves undisturbed monitoring of the experimental environment, accurately recreates the complex stress environment, quantifies the effects of the three factors, provides a scientific basis for the ecological restoration of saline-alkali wetlands, and is convenient to operate and highly repeatable.

The invention discloses an implementation device capable of configuring a data conversion circuit. A register set is configured, a control logic signal is generated, logic conversion processing is conducted on data through the control signal, and finally data filling output is conducted. The device is simple in implementation structure, adopts a synchronous clock design, is convenient for time sequence check and verification, quickly completes data conversion and filling, is convenient to implement and expand on a chip, and enhances the practicability of embedded application; when the method is used for data conversion, the processing flow is simple and easy to control. The device can conveniently generate the data conversion format according to the requirement of the conversion mode so as to meet the application requirement. Therefore, the configurable data conversion circuit is an ideal structure realized by the configurable data conversion circuit.

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 utility model discloses a hovercar, and belongs to the technical field of hovercars, the hovercar comprises an aircraft, a connecting part and a vehicle chassis, the aircraft comprises a rack, a control assembly, a plurality of flight driving assemblies and a plurality of paddles, the control assembly and the plurality of flight driving assemblies are respectively mounted on the rack, and the paddles are correspondingly assembled at the output ends of the flight driving assemblies; the connecting part is detachably connected with the rack or the control assembly; the vehicle chassis comprises a bottom plate and a plurality of wheels assembled on the bottom plate, and the bottom plate is detachably connected with the connecting part. The design is convenient to adjust and improve in trial-manufacture work, vertical take-off and landing and air flight can be smoothly carried out, efficient and accurate simulation of various driving modes of the hovercar is achieved, the structure is simple, operation is convenient and fast, and functions are practical; meanwhile, powerful support is provided for research, development and verification of the key technology of the aerocar, the development process of a new generation of air-ground integrated traffic tools is remarkably promoted, and the method has important engineering application value and leading-edge demonstration significance.

The invention discloses an EEG-based state anomaly detection method and system, a terminal and a medium, and belongs to the technical field of brain-computer interfaces. The method comprises the steps that electroencephalogram signals of a user are collected in real time and preprocessed, and power spectrum density characteristics of a preset frequency band and an inter-brain phase synchronization index are extracted; inputting the features into a tensity quantification model to obtain continuous tensity scores; on the basis of the tensity score and the power change trend of the specific electroencephalogram frequency band, dynamic calibration is carried out in combination with historical baseline data of a user individual, and whether the user is in a violent stress abnormal state or not is judged according to a preset multi-level judgment rule; and if the judgment result is abnormal, triggering a response action. According to the method, through continuous quantification of the tensity, construction of a'tensity-violent state 'strong correlation model and individual dynamic calibration, high-precision, low-delay and low-misjudgment-rate abnormal state recognition is realized, and the method is particularly suitable for home security, public security and vulnerable group protection.

The application relates to a power distribution facility anomaly detection method based on deep learning, and relates to the technical field of power distribution facility anomaly detection. The application collects electric characteristic signals of a power distribution facility at a set sampling rate, selects electric characteristic signals of a non-anomaly time period located on a slow spectrum submanifold as training data, minimizes a loss function, uses a full connection network to learn a mapping matrix from a nonlinear feature vector of the electric characteristic signals to a latent variable on a low-dimensional slow spectrum submanifold of the electric characteristic signals and a linear dynamics matrix in a latent space, in application, collects electric characteristic signals, uses the last corresponding latent variable of the electric characteristic signals and a predicted future latent variable obtained by iteration using the linear dynamics matrix, reconstructs a predicted non-anomaly electric characteristic signal through inverse transformation between the latent variable and the electric characteristic signal, and performs anomaly analysis by using the difference between the predicted non-anomaly electric characteristic signal and an actual electric characteristic signal.

This invention relates to the field of geological modeling and spatial analysis technology, specifically disclosing a method for inferring the migration patterns of chemical elements in a geochemical field. Employing a data-driven approach, it directly learns migration patterns from geochemical data. Compared to traditional numerical simulation methods that rely on precise hydrogeological parameters, this method reduces the dependence on the accuracy of physical models and parameters. Furthermore, this invention models the spatial topological relationships between sampling points using a GAT network, enabling the capture of complex spatial structural relationships, dynamic adjustment of the influence of different neighboring nodes, and clear identification of branching and converging features of migration paths. This effectively characterizes the nonlinear dynamic processes in the migration of chemical elements in a geochemical field.

This invention belongs to the interdisciplinary field of uranium geological exploration information technology and big data processing technology. Specifically, it relates to a method for screening mineralization feature sets of sandstone-type uranium deposits based on the maximum information coefficient (MIC). The method includes: Step S1: Extraction and organization of mineralization feature data; Step S2: Data preprocessing; Step S3: MIC calculation and preliminary ranking of feature values; Step S4: Screening feature thresholds based on inflection point analysis to determine key mineralization features. This method can identify key ore-controlling factors with high correlation to sandstone-type uranium mineralization from geoscientific big data, significantly improving the accuracy, efficiency, and interpretability of subsequent machine learning mineralization prediction models, and providing reliable data support for the selection of uranium exploration target areas.

This invention proposes a method for evaluating the environmental adaptability of ship hull steel based on atmospheric corrosion simulation, enabling a quantitative characterization of its environmental adaptability under complex dynamic environments. Considering the dynamic evolution of the liquid film under the synergistic effects of salt deliquescence and droplet evaporation in the marine atmosphere, and the nonlinear characteristics of corrosion degradation of ship hull steel under the influence of the dynamic liquid film, a dynamic liquid film model is constructed by coupling key environmental factors. Corrosion process simulation is conducted using corrosion electrochemistry principles, and accelerated testing is used to estimate key model parameters. This establishes a quantitative calculation method for the environmental adaptability index of ship hull steel under dynamic environments, improving the environmental adaptability evaluation system for marine metallic materials and providing scientific support for ship structural reliability design, corrosion protection measure optimization, and service life prediction. This invention requires no additional complex scenario adaptation, is highly operable, and effectively improves the efficiency and practicality of evaluating the environmental adaptability of marine materials.

The invention provides an intelligent homework correcting method based on geometric proof questions. The intelligent homework correcting method comprises a question image analysis step, a reference answer structured analysis step, a student answer semantic normalization step and a proof path matching judgment step. According to the method, a user-defined corner name in a student graphic label is efficiently and accurately analyzed, angle semantic expression is unified, structured analysis is carried out on a student written proof text, and a logic derivation path is extracted, so that whether an effective reasoning chain from question condition derivation to conclusion is formed or not is judged; and the understanding ability of custom labels of students and the structured judgment ability of logical reasoning chains are obviously improved.

The invention relates to the technical field of personnel position detection based on electronic equipment, in particular to a personnel position real-time identification method. A personnel position real-time identification method comprises the steps that firstly, one detection unit of a pressure sensor, an infrared induction unit and a millimeter wave radar is used for detecting the position of a person, and the detected position of the person is marked as a first target position; performing personnel detection on the first target position by using another method, verifying the position of personnel in the first target position, and marking the adjusted target range as a second target position; and finally, verifying the second target position by using the other one, verifying the position of a person in the second target position, and marking the adjusted target range as a third target position. The three detection units are used for detection in sequence, the target area can be verified step by step conveniently, the accuracy degree is higher, and the problem that in the prior art, false detection is caused by the adoption of a single detection unit, and consequently the experience of visitors is affected is solved.

The invention relates to the technical field of Internet of Things security, and discloses a zero-trust-based RPL Internet of Things attack data set generation method and system. According to the generation method, an RPL attack library is constructed, an RPL communication network is established, combination use of multiple types of attacks is met, diversified Internet of Things simulation scenes are constructed, zero-trust identity authentication is carried out on Internet of Things nodes in the simulation scenes, and strict continuous evaluation verification is carried out. Acquiring a local network original data packet formed in the RPL routing communication process, integrating the authentication result data and the local network original data packet to form an original basic data set, processing the original basic data set, labeling, verifying and processing the data set, storing the verified data set, and in a simulated Internet of Things environment, storing the verified data set in the RPL routing communication process. A high-quality and multi-scene data set is obtained, and the training requirements of safety detection and the like of subsequent models are met.

The embodiment of the invention discloses a chip kernel performance verification method and device and electronic equipment, relates to the technical field of integrated circuits, and aims to conveniently verify the performance of a to-be-verified object. The method comprises the following steps: acquiring a performance verification file from a preset file library; the performance verification file comprises a to-be-verified object and a first verification environment, and the first verification environment is a verification environment established based on a first verification process; running the first verification process to call a compiling tool to compile the performance verification file; if compiling succeeds, an object to be verified is determined from the performance verification file; receiving a verification preparation instruction; according to the verification preparation instruction, obtaining a to-be-verified object and a second verification environment, and performing performance verification on the to-be-verified object according to the second verification environment; the second verification environment is a verification environment established based on a second verification process, and the second verification process is a verification process based on general verification methodology. The chip performance verification method and device are suitable for chip performance verification.

The application discloses a kind of tumor angiogenesis simulation methods, including the blood vessel network topology including environment pixel point and blood vessel pixel point generated based on the medical image of patient;Based on the average path length and step length adjustment factor, chemotaxis weight, bifurcation number range and bifurcation probability of related data such as blood vessel tip of blood vessel network topology are constantly updated;And the bifurcation number of each iteration blood vessel tip and the branch length of each branch after bifurcation are calculated based on the update result of each iteration, and the update of blood vessel network topology is completed based on the bifurcation number and the branch length of each branch after bifurcation calculated, constantly circulate until reaching simulation condition.The application quantifies the transport efficiency of blood vessel network by global function index average path length, realizes the evaluation whether blood vessel network presents efficient local characteristics by clustering coefficient and average path length, guarantees that the blood vessel network obtained by simulation is same with real network.

This invention discloses an address configuration circuit and system. The address configuration circuit includes: a resistor string and n address setting modules; n≥2, where n is an integer. The resistor string is connected in series between the input terminal and the ground terminal of the address configuration circuit; a cascaded output terminal and n voltage divider output terminals are led out from the resistor string. The number of resistors connected between the cascaded output terminal and the ground terminal of the address configuration circuit is less than the number of resistors in the resistor string; the number of resistors connected between different voltage divider output terminals and the ground terminal of the address configuration circuit is different; the resistor string is used to convert the input signal to the address configuration circuit into a cascaded output signal and n voltage divider signals; each address setting module is electrically connected to each voltage divider output terminal of the resistor string; the address setting module is used to generate an address setting signal based on the voltage divider signals; the n address setting signals constitute the address configuration signal. This invention can improve the stability of the address configuration circuit and the accuracy of address configuration.

The application relates to a multilingual news abstract extraction method based on reinforcement subgraph mining, and belongs to the technical field of natural language processing and artificial intelligence. The application is proposed in view of the problems of the traditional extractive abstract method, such as insufficient coherence between sentences, much redundant information, low abstract quality and the like in long document processing, and comprises the following steps: document multi-level semantic heterogeneous graph construction and initialization; feature enhancement is performed on the sentence nodes through a heterogeneous graph hierarchical structure encoder, a global context encoder and an extraction history encoder; key subgraph mining is strengthened; the abstract extraction process is modeled as a multi-step Markov decision process, key sentence nodes are dynamically selected based on a sentence-level feature graph to form an abstract subgraph, and the selection process is optimized through a reinforcement learning strategy. The application is suitable for automatic abstract generation tasks of long texts such as scientific literature, academic papers and long news reports, and has good interpretability, adaptability and abstract quality.

The application belongs to the field of medical information technology and artificial intelligence assisted diagnosis, and discloses an abnormal fetal heart monitoring mode recognition method and system based on a fetal monitoring atlas. The method obtains fetal heart rate and uterine contraction pressure time sequence signals and performs preprocessing to obtain a reconstructed sequence; physiological events are recognized from the reconstructed sequence and attribute nodes are constructed, each node being associated with an attribute vector representing the physiological characteristics of the event; a multi-modal heterogeneous time sequence atlas is constructed according to the time sequence relationship and physiological coupling relationship between the nodes; based on causal path constraints and delta t sequence evolution rules, structured consistency is determined in the real-time atlas, local subgraphs that meet the causal evolution path are recognized, and abnormal patterns are recognized; based on the recognition result, a comprehensive risk value is calculated and warning information is output. The application explicitly expresses the causal relationship between uterine contraction and fetal heart through the atlas structure, combines fuzzy matching and contrast learning, and realizes high-precision, high-robustness and high-explainability abnormal recognition.

This application provides a modeling method, a modeling apparatus, an electronic device, and a storage medium; the modeling method includes: constructing a fourth model based on a first model, a second model, and a third model; the fourth model is used to predict the lifetime of an isotope power source; wherein, the first model characterizes the effect of device temperature difference decay on the lifetime of the isotope power source; the second model characterizes the effect of device material irradiation damage decay on the lifetime of the isotope power source; and the third model characterizes the effect of device material thermal aging on the lifetime of the isotope power source.

This disclosure provides a method, apparatus, device, and storage medium for calibrating roadside sensors, relating to the field of artificial intelligence technology, and particularly to the fields of vehicle-road cooperation and intelligent transportation technology. This solution allows users to easily calibrate the parameters of roadside sensors in a list online to obtain the corresponding parameters. This enables unified storage and management of the parameters corresponding to each roadside sensor in the list. When a user needs to cross-verify a specific roadside sensor in the list, they can conveniently verify its calibrated parameters against those of other roadside sensors installed at the same intersection. This allows for recalibration of the corresponding roadside sensors when errors are significant, ensuring the accuracy of the calibrated parameters for each roadside sensor.

The application discloses a kind of geological disaster-oriented long oil and gas pipeline risk intelligent evaluation methods, comprising: based on pipeline working condition (steel grade, wall thickness, weld, corrosion, operating pressure etc.) and multi-source heterogeneous data (DEM, geology, InSAR, rainfall, historical disasters, pipeline monitoring etc.) are segmented dynamically;Adopt multi-model integrated prediction landslide, collapse, debris flow, settlement etc. Disaster-prone E;Construction oil and gas special vulnerability index system and failure consequence index system, and through AHP and entropy weight combination empowerment (including difference coefficient λ) calculate vulnerability index V and consequence index C;According to R = E * V * C Or weighted linear model calculates segmented risk value and is divided according to grade;Based on contribution degree analysis identifies leading factor and dynamically updates risk result under monitoring trigger condition, outputs key risk section, risk change trend and inspection / emergency suggestion.This method considers oil and gas working condition characteristics and data driving ability, is convenient for engineering implementation and decision support.

The invention provides an inquiry method and device, electronic equipment and a storage medium. The method comprises the following steps: calling an abstract agent to generate a historical health abstract of a patient based on historical health data of the patient; calling an interaction agent to perform inquiry interaction with the patient based on the historical health abstract, and generating an initial medical record of the patient based on interaction information of the historical health abstract and the inquiry interaction; calling a reasoning agent to perform diagnosis reasoning based on medical domain knowledge, the historical health abstract and the initial medical record to obtain preliminary diagnosis information of the patient; sending the preliminary diagnosis information to a doctor terminal, and receiving diagnosis information returned by the doctor terminal; and calling a reasoning agent to generate an illness state analysis report of the patient based on the medical domain knowledge and the diagnosis information. According to the method, the device, the electronic equipment and the storage medium provided by the invention, the intelligent coverage of each link in the inquiry process is realized by the cooperation of a plurality of agents, so that the diagnosis and treatment efficiency and quality are improved.

The application discloses a GO-FLOW automatic modeling and analysis method and system based on a system flowchart, an electronic device and a storage medium, and the method comprises the following steps: through analysis and reading of a system CAD or Visio data structure file, system flow structure and equipment composition information are identified and extracted; further, in combination with consideration of general system equipment division and equipment failure modes, a GO-FLOW componentized model of system equipment is constructed; according to a modelized mapping relationship of a GO-FLOW operator, a system model data structure file is automatically generated; finally, the generated system model file is imported into a GO-FLOW computing engine, and system reliability analysis is realized.