389results about How to "High feasibility" patented technology

According to the privacy enhancement type (k, d)-truss community search method for the social network, a novel KTG tree structure is constructed by fusing k-truss and G-tree indexes. According to the index structure, hierarchical community decomposition of a social graph and social distance information are fused, a refined boundary vector coding scheme is designed to support efficient distance calculation, and a double-cloud-server non-collusion architecture integrating improved homomorphic encryption and matrix encryption technologies is constructed. Through a two-stage security query process of first structure filtering and then distance verification, on the premise of protecting full-process privacy of a graph structure, a query intention, a distance matrix and an intermediate calculation result, efficient and accurate search of a close community in a large-scale social network is realized. The method is suitable for various scenes such as social recommendation, risk control, public opinion analysis and anti-fraud, and the problems of privacy disclosure and calculation efficiency in social network analysis are effectively solved.

The invention provides an NoC low-delay data transmission method based on a dynamic routing algorithm, relates to the technical field of data transmission, and aims to solve the technical problems that an existing NoC routing algorithm cannot adapt to a link dynamic load, is lack of congestion trend prejudgment, is slow in path search convergence and is insufficient in QoS differential scheduling. The method comprises the following steps: constructing a dynamic sensing module containing a double-branch LSTM time sequence prediction model, collecting states such as link bandwidth and queue length in real time, and predicting a congestion trend in 50-100ms in the future; constructing a multi-objective evaluation function taking delay as a core, and dynamically adjusting the weight according to the QoS level; solving an optimal path by adopting an improved ant colony algorithm which introduces a congestion penalty and pruning strategy; during transmission, dynamic reselection is triggered through a pre-calculation + fast matching mechanism; and iteratively optimizing the prediction model based on incremental learning. According to the method, congestion is avoided in advance, the path search efficiency and the transmission reliability are improved, the delay is remarkably reduced compared with a traditional algorithm, and the method is adaptive to delay sensitive scenes such as a high-performance processor and an AI chip.

The invention provides a multi-reflection superposition enhanced microwave displacement measurement method and system, and the method comprises the steps: S1, constructing a microwave multi-reflection propagation path, enabling a microwave radar to transmit electromagnetic waves to the microwave multi-reflection propagation path as a transmission signal, and receiving a corresponding echo signal; s2, extracting length change information of a microwave multi-reflection propagation path according to the echo signal; s3, establishing a linear superposition relation model between the total length of the microwave propagation path and respective displacements of W reflection surfaces in the microwave multi-reflection propagation path; w2; and S4, based on the linear superposition relation model, displacement information of the corresponding reflection surface is obtained and output. According to the invention, a larger phase variation can be obtained under the condition of small displacement or weak vibration, so that the measurement sensitivity is improved and the signal-to-noise ratio is improved.

The invention discloses a two-stage space-time diagram network and multi-source information fusion time sequence probability prediction method and device, and relates to the technical field of artificial intelligence and big data analysis. The method comprises the following steps: acquiring historical wind speed sequence data and corresponding target variable sequence data; preprocessing the data, and constructing a training sample according to a preset time sliding window; constructing a time sequence probability prediction framework of the two-stage space-time diagram network and multi-source information fusion; based on the fluctuation correlation of the historical sequence data, constructing an adjacent matrix between nodes; inputting the training sample and the adjacent matrix between the nodes into a wind speed prediction model, training the model through a designed threshold perception loss function of a wind speed-power nonlinear relationship, and outputting a multi-node wind speed prediction probability of a first stage; and inputting the multi-node wind speed prediction probability and the multi-source environmental factor data into the gradient boosting tree model for second-stage prediction, and outputting a multi-node wind power prediction result. According to the invention, prediction errors can be reduced.

The invention discloses an alloy smelting batching scheme generation method and system, particularly relates to the technical field of metal material production and supply chain collaborative optimization, and is used for solving the problems of uncontrollable execution, cost waste and quality risk caused by disconnection of static parameters and a dynamic supply chain in an existing batching scheme. The method comprises the following steps: acquiring target alloy component demand parameters, raw material inventory allowance and purchase cycle parameters; identifying a dynamic constraint key material with a supply interruption risk; establishing a dynamic constraint model containing an inventory safety buffer threshold based on the historical consumption volatility; candidate batching schemes are generated through multi-level optimization; verifying inventory performability and compatibility of alternative material components; sorting and outputting the effective schemes according to the cost and inventory suitability; through supply chain risk quantification and dynamic constraint modeling, the feasibility of a batching scheme is remarkably improved, and production halt loss and potential quality hazards caused by supply interruption or blind substitution are reduced.

The invention relates to an engineering potential safety hazard detection method based on a multi-modal large model. The method comprises the following steps: acquiring an on-site monitoring image of a target scene; identifying a key entity in the field monitoring image, and extracting positioning information of the key entity; generating a depth map based on the on-site monitoring image; based on the positioning information of the key entity, combining with the depth map, associating the positioning information and the depth information for the key entity, and generating a scene description text; based on the on-site monitoring image, the depth map corresponding to the on-site monitoring image and the scene description text, constructing a multi-modal input packet; inputting the multi-modal input packet into a learned engineering safety domain knowledge base and a visual language large model subjected to instruction fine tuning, and outputting a hidden danger judgment result; the instruction fine tuning of the visual language large model is based on a hidden danger inference chain data set, the data set has hidden danger images corresponding to hidden danger items in an engineering safety field knowledge base and annotation data of each hidden danger image, and the annotation data comprises step result data corresponding to each hidden danger detection step.

The invention provides an environmental protection equipment energy consumption optimization and energy-saving regulation and control method based on multi-source data fusion, and relates to the technical field of environmental protection equipment energy-saving control, and the method comprises the steps: collecting the operation data of environmental protection equipment, carrying out the multi-scale feature extraction, recognizing the energy consumption abnormity through combining the energy efficiency curve reconstruction, and carrying out the energy-saving control of the environmental protection equipment; energy consumption sensitive parameters are extracted, energy-saving space is calculated based on load fluctuation, and an optimized parameter adjusting scheme and an optimized time sequence control sequence are generated by integrating the environment load change rate and the equipment thermal inertia coefficient. The energy consumption abnormity can be accurately identified, the energy-saving space is scientifically quantified, the intelligent optimization and dynamic regulation and control of the energy consumption of the environmental protection equipment are realized, and the operation efficiency of the equipment is obviously improved.

A batch process model-free output feedback control method with non-repetitive interference belongs to the technical field of industrial process control, and specifically comprises the following steps: step 1, giving a mathematical description for an optimal tracking control problem of a non-repetitive batch process; 2, designing an optimal control law based on output feedback; 3, a game Q function construction method based on two-dimensional output feedback in the intermittent process; 4, solving a two-dimensional output feedback problem of batch operation by utilizing reinforcement learning; 5, solving an optimal control strategy based on output feedback through iteration to enable the optimal control strategy to be finally converged to an ideal optimal value; according to the method, the problem that a traditional method for processing the complex characteristics of a two-dimensional system is too tedious is solved, through the output feedback control method based on reinforcement learning, the method does not depend on a system model, the influence on the control performance is reduced, and the control effect is greatly improved.

The invention discloses a rocket fault reconstruction method for ensuring the safe height of an orbit under random factor disturbance. The method comprises the following steps: S1, establishing a deterministic trajectory optimization model of a carrier rocket; s2, on the basis of the deterministic trajectory optimization model, introducing random disturbance representing initial state deviation and engine thrust deviation, and establishing a random trajectory optimization model of the carrier rocket; s3, performing convex processing on the random trajectory optimization model, and converting an original problem including a nonlinear term and a non-convex constraint into a convex optimization problem; and S4, solving the convex optimization problem after the convex processing by adopting a sequence convex algorithm, and obtaining a rocket fault reconstruction trajectory capable of ensuring the safe height of the orbit under the disturbance of random factors. According to the method, efficient online solving of a strong nonlinear non-convex random trajectory optimization problem can be realized, so that a fault reconstruction trajectory which can strictly guarantee the safety height of an injection orbit in the probabilistic sense is generated.

The invention belongs to the technical field of chemistry, and particularly relates to a water-based stable transdermal preparation based on a structural nanoemulsion and a preparation method of the water-based stable transdermal preparation. 1% to 10% of a polyether block copolymer; 5%-20% of a co-emulsion; 0.1% to 15% of an active ingredient; and the balance of deionized water. Through a compounding system of an amino acid surfactant and a gemini surfactant and in combination with the synergistic effect of a specific polyether block copolymer, a nanoemulsion drug delivery system with a stable structure is constructed. Through a compound system of the amino acid surfactant and the gemini surfactant and by combining the synergistic effect of the polyether block copolymer, a nano-emulsion drug delivery system with a stable structure is constructed, and the nano-emulsion drug delivery system has good long-term storage stability and temperature adaptability, is not easy to layer and is uniform in particle size distribution.

The application provides a logistics transportation management method and system based on artificial intelligence, relates to the field of logistics transportation, and solves the technical problems that the prior art is difficult to balance real-time performance, distribution feasibility and resource utilization efficiency in the sudden interruption scene of a logistics vehicle, resulting in slow scheduling response, frequent secondary conflicts or failure of high-value order fulfillment. The method comprises the following steps: obtaining a set of orders to be delivered by a target vehicle at present and real-time position information; based on a preset hard constraint condition, screening candidate vehicles and constructing a task migration feasibility graph; inputting the task migration feasibility graph into a pre-trained lightweight graph neural network model to output the compatibility scores of each candidate vehicle for each order to be delivered in the order set; based on the compatibility scores, evaluating the urgency of the order to be delivered; and based on the urgency of the order to be delivered, updating the delivery task scheme of each candidate vehicle. The application is used in the process of logistics transportation.

This invention discloses a method for overlapping construction of waterproofing systems in existing subway lines. It relates to the field of underground engineering waterproofing construction technology and includes: Step 1, current status investigation and deformation assessment; Step 2, overlapping structure system design; Step 3, key material selection and process matching; Step 4, refined overlapping construction process; and Step 5, full inspection after each process. This invention's method for overlapping construction of waterproofing systems in existing subway lines, through Step 1, involves structural deformation monitoring and analysis and diagnosis of the existing waterproofing layer; Step 2, involves deformation adaptation structure design and differential deformation compensation design; Step 3, involves material selection and process innovation; Step 4, involves base treatment, interface treatment, expansion joint and node construction, and reinforcement layer construction; and Step 5, involves process inspection. This method, tailored to the characteristics of existing subway lines, enables the effective combination of different waterproofing materials, adapts to continuous deformation, and ensures long-term reliability.

The application discloses a video instantaneous heart rate detection method based on time-frequency spectrum conversion and an image enhancement network, and comprises the following steps: 1, selecting a face region of interest from a video to obtain a target BVP time sequence; 2, converting the target BVP time sequence into an original time-frequency spectrum through time-frequency spectrum conversion; 3, establishing an image enhancement network to enhance the original time-frequency spectrum and obtain an enhanced time-frequency spectrum; 4, training the image enhancement network; and 5, extracting an instantaneous heart rate value from the enhanced time-frequency spectrum. The application combines time-frequency spectrum conversion and the image enhancement network, extracts a time-frequency spectrum containing instantaneous heart rate information from a face video, can improve the accuracy of instantaneous heart rate detection, and thus provides a new method for non-contact instantaneous heart rate detection based on a video.

The present application relates to the field of intelligent traffic parking scheduling, and particularly relates to a parking resource comprehensive scheduling strategy optimization method and system based on multi-region cooperation, which specifically as follows: collecting multi-region and multi-type parking resources, commuting parking demand, illegal parking risk and road network operation data according to scheduling period, constructing parking cooperative monitoring sample through standardization processing; calculating time-sharing sharing potential index, underground priority access intensity and road overflow risk elasticity index, constructing hierarchical directed ant colony search graph with heuristic information written; introducing capacity constraint self-repairing mechanism and congestion degree pheromone updating mechanism, solving Pareto solution set through multi-objective ant colony optimization, screening optimal compromise scheme combining fuzzy membership and dynamic preference weight, outputting parking guidance instruction and realizing rolling closed-loop iteration. The present application can realize time-sharing cooperative deployment of parking resources in residential and office areas, balance various parking load, and improve overall utilization efficiency of parking resources.

The utility model discloses a bending parallel dog bone hole mild steel plate high-ductility mortar energy dissipation and shock absorption device which is composed of an upper connecting steel plate with a round hole, a lower connecting steel plate, a lower connecting steel plate, an upper connecting steel plate with a round hole, a lower connecting steel plate, a lower connecting steel plate, a lower connecting steel plate, a lower connecting steel plate and a lower connecting steel plate, wherein the upper connecting steel plate is connected with a lower flange of an H-shaped steel frame beam; the upper connecting steel plate and the lower connecting steel plate are welded between the upper connecting steel plate and the lower connecting steel plate, and the left-side and right-side blocking skin dog-bone hole mild steel plate, the bending parallel dog-bone hole mild steel plate and the front-back blocking mild steel plate are welded between the upper connecting steel plate and the lower connecting steel plate. And the upper and lower connecting steel plates are connected with the high-strength bolt system of the steel frame-supporting structure. Under the action of strong shock, the front and rear plugging mild steel plates are subjected to buckling deformation energy dissipation and shock absorption, the sections of the parallel dog bone hole mild steel plates are subjected to nearly-equal-strength bending plastic deformation consumption shock absorption, and the high-ductility mortar combined with the mild steel plates is subjected to whole-process consumption shock absorption of cracking, yielding and damage, so that the energy dissipation and shock absorption effect of the device can be effectively improved.

The invention discloses a method for carrying out nine-fold breeding by utilizing female gametes, and relates to the technical field of biological breeding. Comprising the following steps: step 1, pollinating hexaploid persimmon pollen to a'rattan royal house 'containing 2n eggs; 2, collecting young fruits which are born for 65-70 days after pollination, stripping seeds, putting the seeds into a sterilized triangular flask, treating the seeds for 30 seconds in an ultra-clean workbench by using 70% ethanol, pouring out the seeds, adding a 1% NaClO solution, soaking the seeds for 10 minutes, and shaking the seeds once every 3-4 minutes. According to the method for carrying out nine-fold breeding by utilizing female gametes, in persimmon breeding, compared with a 2n pollen path, the 2n egg path is higher in feasibility, 2n eggs and complete male germplasm with good pollen traits are hybridized, pollination populations are expanded, and polyploidy seedless materials can be obtained.

The application discloses a coking ammonia distillation wastewater filter tar scale cleaning agent and a preparation method thereof, and relates to the technical field of industrial cleaning agents. The cleaning agent comprises the following components in mass percentage: N-methyl pyrrolidone 30-40%; ethylene glycol monobutyl ether 1-3%; sodium dodecyl benzene sulfonate 5-9%; sodium polyepoxysuccinate 1.5-3.5%; sodium silicate 0.5-1.5%; and deionized water in the rest. The application greatly reduces the content of ethylene glycol monobutyl ether and optimizes the compound system of the main solvent and the surfactant, completely solves the normal-temperature stratification problem of the traditional water-based cleaning agent, realizes VOC≤8.5%, cleaning rate≥98.5%, stable storage for≥6 months under the conditions of shade, ventilation and avoidance of direct sunlight, recyclable use for 2-3 times, mild preparation process without foaming problem, and easy industrial production.

The present application belongs to the field of power system intelligent inspection and computer vision technology, and provides a kind of transmission line hidden danger target detection test adaptive method and system, obtains inspection image, utilizes pre-training detector to carry out forward inference to the inspection image, generates original prediction set, and the original prediction set includes prediction frame coordinates, class label and confidence score;Geometric verification is carried out, and reasonable geometric prediction set is obtained;Carry out spatial neighborhood clustering, obtain multiple candidate clusters, calculate the scale dispersion of the area of the prediction frame in each candidate cluster, group according to the class label, dynamically cluster the prediction frame in the group, perform weighted average on the prediction frame coordinates with the confidence score as the weight, calculate the fusion confidence, obtain the refined pseudo label set, use it as the supervision signal, calculate the detection loss, and iteratively update the model parameters through the optimization algorithm until the iteration number is satisfied.The present application improves accuracy, versatility and engineering reliability.

The invention discloses a model prediction control vehicle obstacle avoidance method based on road and obstacle modeling, and belongs to the technical field of automatic driving and intelligent vehicle trajectory tracking control. Aiming at the problems of insufficient environment modeling, rigid constraint processing, poor limited perception scene adaptability and the like of traditional model prediction control, the invention provides a model prediction control method fusing road and obstacle models. According to the method, constructed structured road boundary and obstacle information is embedded into an optimization target of model prediction control in a continuous differentiable penalty term form, so that soft constraint fusion of a road rule and a safe distance is realized. According to the method, the environmental adaptability and the control reliability in a limited perception structured scene are remarkably enhanced while the driving safety and the track smoothness are improved.

The present application relates to the technical field of smart park management and intelligent traffic, in particular to a smart park parking decision optimization method and system, comprising the following steps: S1: collecting multi-dimensional original data related to park parking through multi-source sensing equipment, and preprocessing the collected original data. Through the weighted feature fusion and coarse-fine granularity adaptive prediction model system, the present application dynamically optimizes the prediction accuracy combined with the online learning mechanism, accurately outputs the multi-time and space granularity parking demand and traffic situation results, provides reliable data support for decision making, and according to the cloud-edge-end collaborative architecture and high-fidelity digital twin simulation environment, through the hierarchical dynamic multi-objective optimization algorithm and iterative verification mechanism, generates the optimal parking scheduling and traffic guidance strategy that meets the constraints of complex scenes and takes into account multiple demands, greatly improves the scientificity and feasibility of decision making.

The invention relates to the field of phased radars, and discloses an active phased array radar calibration method, which is used for improving the accuracy of actually measured phase data. Comprising the following steps: calculating theoretical excitation phases of radiation units according to an antenna array physical geometric structure and a target beam directional angle; enabling the antenna to sequentially excite the radiation units and collect coupling signals in a single-channel mode, and performing analysis to obtain an actually measured amplitude, a phase and a phase deviation; synthesizing the theoretical excitation phase and the phase deviation to generate an actual emission phase, and constructing a phase compensation lookup table; and after compensation by using the lookup table, measuring the actual directional diagram, and if not, performing fine adjustment. The calibration precision and reliability are improved, and the high-precision detection requirement of the active phased array radar can be met.

The present application belongs to the technical field of traditional Chinese medicine composition, and relates to a traditional Chinese medicine transdermal external preparation for treating vulvar hypopigmentation disease. The preparation is a paste prepared by mixing traditional Chinese medicine powder and horse oil. The traditional Chinese medicine powder is composed of the following raw materials by weight: Xuchangqing 10-12, Pugongying 10-15, Difusiduo 12-15, Tuzifuding 12-15, Baiji 10-15, Huzhang 9-12, Quansie 6-10, Diyu 10-12, Xuezhi 10-12, Danggui 6-10, Rushang 6-10, Miedu 6-10, Bingpian 1-3. The traditional Chinese medicine transdermal external preparation has definite and significant effects on vulvar hypopigmentation disease, especially in relieving intractable pruritus, promoting pigment recovery and improving skin sclerosis / atrophy. The traditional Chinese medicine transdermal external preparation has high safety, few adverse reactions and low recurrence rate.

The application provides a method and device for treating wastewater by combining a suspended filler floating bed and a soil infiltration system, and the method comprises the following steps: S1, breeding wastewater is treated by the suspended filler floating bed after passing through a hydrolysis tank, and effluent is treated in a sedimentation tank, and wastewater of the suspended filler floating bed is returned to the suspended filler floating bed for secondary treatment; S2, wastewater of the sedimentation tank is returned to the hydrolysis tank; and S3, effluent of the sedimentation tank is introduced into a soil underground infiltration system. The system provided by the application is beneficial to further strengthening the effects of denitrification, phosphorus removal and removal of suspended solids, and solves the problems of low dissolved oxygen content of influent and wastewater in the system, which is not conducive to the growth of nitrifying bacteria, and low effective volume utilization rate. In the use process, the filler does not need to be replaced, and mechanical aeration equipment does not need to be added, and the system has the advantages of low investment cost, no need to add chemical agents for treatment, obvious effect, not easy to breed mosquitoes, simple operation and management, and beautification of the environment, and has remarkable ecological and economic benefits for promoting deep purification of breeding wastewater.

This application discloses a method, apparatus, and electronic device for operating a microcontroller, belonging to the field of microcontrollers. The method for operating the microcontroller includes: obtaining the microcontroller's execution state based on a first bootloader firmware when the microcontroller restarts; performing a security verification on a target executable firmware based on a second bootloader firmware if the execution state indicator meets a first condition; and restoring the microcontroller based on an initial bootloader firmware and an initial executable firmware if the execution state indicator does not meet the first condition. The microcontroller operation method of this application can reduce the risk of device failure or malfunction due to power outages, software operation failures, or logical or version compatibility issues in the executable firmware itself during the process of upgrading the bootloader firmware via the executable firmware, thereby improving the resilience and reliability of upgrading the bootloader firmware via the executable firmware.

The invention relates to a method for optimizing struvite production parameters based on response surface method and Minteq combined regulation and control, and belongs to the technical field of parameter optimization. The invention discloses a method for optimizing struvite production parameters based on response surface method and Minteq combined regulation and control. The method has the following advantages: (1) the pH can be regulated and controlled according to the concentration of heavy metals in wastewater, the concentration of bicarbonate maximizes the recovery rate of phosphorus, the occurrence of heavy metals in struvite products is minimized, and the yield of the struvite products is improved; optimal process parameters are provided for safe and healthy application of agricultural soil fertilization; (2) the adopted response surface method has the characteristics of simple operation, high feasibility and accurate prediction; (3) regulation and control can be performed according to the concentration and alkalinity of heavy metals contained in phosphorus-containing wastewater of pig manure wastewater, and high-quality phosphorus recovery of different types of wastewater is realized; and (4) parameter regulation and control can be carried out according to the measured wastewater with phosphorus recovery value, the dosage of sodium hydroxide is saved, and the cost is greatly saved.

The application discloses a stable domain constraint trajectory planning and control method for a modular distributed electric drive heavy load vehicle, comprising the following steps: constructing a nonlinear dynamics model of the modular distributed electric drive heavy load vehicle, fitting a tire lateral force model through a rational polynomial, and establishing a vehicle system state space expression based on the rational polynomial form; adopting a sum of squares planning method to estimate the stable domain of the vehicle under different vehicle speeds, road adhesion coefficients and front, middle and rear wheel turning angles, and analyzing the influence of each state quantity on the shape and boundary of the stable domain; embedding the stable domain constraint into a trajectory planning layer based on a quintic polynomial to generate an obstacle avoidance trajectory meeting the dynamics stability; designing a multi-axle proportional steering strategy based on a steady state assumption, and combining a nonlinear model predictive controller to realize trajectory tracking control, so that the stability and control feasibility of the vehicle in a high-speed dynamic obstacle avoidance process are ensured. Through construction of a high-speed dynamic obstacle avoidance simulation scene, the effectiveness, stability and control feasibility of the stable domain constraint trajectory planning and control framework are verified.

The invention discloses an inland river electric ship intelligent navigation and energy management integrated control system and method. The system comprises a perception and communication layer, a central decision and calculation layer and an execution and energy layer. The sensing layer obtains multi-source information, including surrounding ship AIS, ship positioning and ground speed, external real-time water flow, ship lock scheduling, channel static geography and actually measured water flow information. The central decision-making layer comprises a data fusion and water flow compensation module which aligns information and solves the real-time water speed through vector fusion; the sailing resistance prediction module is used for predicting future resistance based on the water speed and the geometric information of the navigation channel; and the energy management predictive control module is used for generating an optimal power distribution instruction through rolling optimization based on the water speed and the predictive resistance. The execution layer comprises a composite power supply and an electric propulsion system and is used for executing instructions. Integrated control is achieved through AIS enhanced sensing and water flow compensation, and the accuracy, safety and economical efficiency of ship control are improved.

The application discloses a hydropower station time-sharing power generation benefit dynamic control method fusing power grid load demand, obtains multi-dimensional operation data of a hydropower station and power grid time-sharing load and electricity price data, constructs a data correlation model based on an attention mechanism, generates a fusion feature data set through dynamic weight distribution, takes time-sharing power generation benefit maximization as an objective function, combines reservoir water balance, unit output limitation and downstream ecological flow constraints, introduces a deep reinforcement learning algorithm to construct a dynamic control model, trains the model and optimizes parameters by using historical and simulation data, then inputs real-time data to generate an optimal time-sharing power generation control scheme, issues an instruction and monitors output deviation, and realizes dynamic control; the method can accurately match power grid load and time-sharing electricity price, improves power generation benefit while meeting multiple constraints, and is suitable for various hydropower station dispatching scenarios which need to consider power grid response and benefit optimization.

The application discloses a student programming answer prediction method combining semantic understanding and structured modeling, collects student programming homework data and pre-processes the data to obtain data samples, translates the data samples to obtain an English feature set; uses low-rank adaptation to fine-tune a pre-trained semantic understanding model, constructs input features, and predicts an answer correctness probability; performs graph neural network structured modeling based on the association relationship between problems and concepts, performs message propagation and feature updating to obtain an embedding set, inputs the embedding set and student embedding into a prediction layer to obtain a probability of answering a question correctly; and inputs the probability of answering a question correctly and the probability of answering a question correctly after fusion into a multilayer perceptron for nonlinear mapping to predict the probability of answering a question correctly. The application solves the problems of difficulty in effectively processing non-standardized codes submitted by students, insufficient semantic understanding of question texts and low prediction accuracy in programming knowledge tracking, and provides a scientific basis for personalized teaching and learning resource scheduling.

This invention relates to the field of nondestructive testing (NDT) technology, solving the technical problems of large measurement errors and insufficient detection accuracy in existing technologies under lift-off fluctuations caused by changes in coating thickness. Specifically, it relates to a pulsed eddy current lift-off and thickness decoupling method based on the characteristic quantity of the frequency domain amplitude centroid and the time domain ratio. Based on a pulsed eddy current analytical model, the pipe under test with a coating layer is equivalent to a three-layer flat plate structure, and the time-domain induced voltage signal of the pipe is obtained through a detection platform. A fast Fourier transform is performed on the time-domain induced voltage signal to obtain the corresponding frequency-domain induced voltage spectrum, and the frequency-domain amplitude centroid used to characterize the lift-off height is calculated based on the frequency-domain induced voltage spectrum. This invention uses the raw induced voltage signal as the analysis object, eliminating the need for complex preprocessing. The signal processing flow is simple and efficient, reducing computational complexity while ensuring detection accuracy, thus improving detection efficiency and engineering application feasibility.