23results about How to "Guaranteed rigor" patented technology

This application relates to an event-driven method and computing device for recognizing revenue from intra-group transactions. The method includes: acquiring a transaction order and determining its type; if the transaction order is an intra-group transaction order, acquiring its triggering event; if the triggering event is a key business completion event, generating a cost recognition voucher for the purchaser of the transaction order and a revenue recognition voucher for the seller of the transaction order; wherein the key business completion event represents a business operation event indicating that the relevant performance obligations have been fulfilled. This achieves a fundamental shift from employee-based identification and triggering to system-based perception and response, improving the timeliness and accuracy of financial processing, thereby reducing operating costs and increasing processing efficiency.

This invention discloses an I2C master-slave device joint verification platform, comprising: a design module including an I2C master device and an I2C slave device, which are connected via data lines and control lines; an interface including a first interface and a second interface; and a verification module including a first proxy module, a second proxy module, and a comparator. The first proxy module is connected to the first interface, the second proxy module is connected to the second interface, and the first and second proxy modules are connected via the comparator. The first proxy module is configured to capture first write transaction data / second read transaction data of the I2C master device through the first interface, the second proxy module is configured to capture first read transaction data / second write transaction data of the I2C slave device through the second interface, and the comparator is configured to compare the first write transaction data / second read transaction data with the first read transaction data / second write transaction data. This invention also discloses an I2C master-slave device joint verification method.

The invention relates to the technical field of cultural relic identification and visual large model fusion, in particular to a ceramic cultural relic full-dimensional identification system and method based on multi-modal visual large model and microscopic feature fusion. After high-quality applicable data are screened, other data are calibrated with the optimal mode as the reference, cross-mode deviation is eliminated, and a data foundation is built firmly; the core features are converted into topological nodes, association strength is calculated, feature association edges with guidance are established, a traceable and explainable identification guidance link is generated, and the strong ceramic identification logic requirement is met; the optimal link is screened to be combined with the pre-training model, and the identification precision and the careful property are balanced by depending on a confidence hierarchical judgment mechanism, so that the black box pain point of the traditional model is effectively solved, and the credibility of the identification result is improved.

The invention discloses a tumble risk assessment method and system based on individualized information, and relates to the technical field of medical assessment and artificial intelligence, and the method comprises the following steps: a data acquisition step, a support period detection step, an individualized feature fusion step, a gait period segmentation step, a feature extraction step, and a time sequence coding step. A risk assessment step; firstly, multi-channel plantar pressure time sequence data of a subject and individualized information of the subject are obtained, and then through five-layer progressive processing, the problems of supporting period self-adaptive detection, gait cycle precise segmentation, multi-dimensional feature extraction, time sequence dynamic modeling and self-adaptive model training are solved respectively. And finally, accurate individual fall risk assessment is realized. Thresholds are automatically adapted for subjects with different physiological features, the gait deterioration trend caused by fatigue is captured through periodic-level double-flow time sequence modeling, and self-adaptive personalized feature learning is achieved through cascaded personalized information layer-by-layer fusion.

This invention relates to the field of road-bridge transition section health monitoring and intelligent transportation technology, specifically to a method for inferring the location of slab breakage in road-bridge transition sections based on vehicle acceleration. The method involves: collecting vibration signals from vehicles passing through the road-bridge transition section using an onboard acceleration sensor; denoising, noise reduction, and normalization of the collected data; extracting the actual acceleration collected by the sensor using wavelet transform and fast Fourier transform; constructing a physical-mechanical model of the road-bridge transition section and a vehicle-road coupled mechanical model to determine the slab breakage status; calibrating the slab breakage status using a Bayesian probability model, constructing a likelihood function and prior distribution; inferring the posterior distribution based on the likelihood function and prior distribution; and calculating the posterior distribution using the MCMC method. This invention infers the location of slab breakage in road-bridge transition sections using vehicle vibration data and Bayesian methods, enabling precise quantification and uncertainty assessment of road defects.

The invention discloses a curriculum commodity personalized recommendation method and device, a terminal and a storage medium, and relates to the field of commodity recommendation. The method comprises the following steps: acquiring client target data and multi-dimensional current situation data to perform state quantification to obtain a quantized state set, constructing a course logic relation graph, mapping knowledge level differences to graph effective nodes, performing topological sorting and time resource filtering to obtain candidate learning paths, and performing learning on the candidate learning paths. And calculating the comprehensive gain value of the candidate learning path, and selecting the path corresponding to the highest value as a personalized recommendation path. Meanwhile, the method also comprises a rapid recommendation step for new customers or data sparse customers. The technical effects of providing a personalized course commodity recommendation scheme according to the actual condition of the customer, improving the accuracy and effectiveness of recommendation, saving the learning time for the customer, improving the learning effect and facilitating the new customer to quickly obtain proper recommendation are achieved.

The invention discloses a subjective and objective combination weighting evaluation method based on variance optimization, and the method comprises the steps: firstly evaluating the relative importance of each index, and obtaining the subjective weight of each index; constructing a sample-index matrix, calculating the information entropy value of each index, obtaining the weight of each index based on the information entropy, removing redundant indexes through the calculation of the index correlation degree and the correlation degree between the indexes, achieving the de-overlapping, calculating the absolute correlation degree of the indexes, and carrying out the normalization to obtain the objective weight of the indexes; setting subjective and objective weight coefficients, carrying out linear addition processing on subjective and objective weights, and on the premise that the sum of constraint condition coefficients is 1, enabling the variance to be as small as possible to obtain the optimal subjective and objective combined weight of each index; and judging subjective and objective weights of the indexes and the consistency of sorting arrays, and determining final weights of the indexes. On the basis of keeping the advantages of the original subjective and objective evaluation method, the advantage complementation of subjective weighting and objective weighting is realized, and the evaluation effect of the evaluation model is improved.

The invention discloses a full-process simulation and blasting pressure prediction method for a weak-rigidity core mold composite material shell, and belongs to the technical field of solid rocket engine integrated explosive forming shell design. The method comprises the following steps: designing an equal residual stress tension system based on a fiber winding layer stress theory; constructing a finite element model in the shell winding process, iteratively optimizing a tension system and determining a stress field and a strain field after winding; taking the stress field and the strain field as predefined fields, constructing a finite element model in the curing process, and calculating the stress field and the strain field after curing; and based on the stress field and the strain field after curing, progressive damage analysis is realized through a three-dimensional Hashin criterion, and the maximum blasting pressure of the shell with the powder is predicted. The problems that in the prior art, a tension system lacks collaborative optimization, simulation cannot cover the whole process, and blasting prediction deviation is large are solved, precise coupling prediction of the process and performance is achieved, and theoretical support is provided for optimization of the integrated forming process.

The invention discloses a non-abandoned pattern rendering enhancement method based on generative image processing. The method comprises the steps of non-abandoned pattern collection, image preprocessing, enhancement generator model construction, discriminator model construction and non-abandoned pattern rendering enhancement. The method comprises the following steps: acquiring original image data through a non-missing pattern; image preprocessing methods of color normalization, random visual confusion, geometric space deformation, multi-scale image generation and data set segmentation are adopted; the enhancement generator model outputs a non-abandoned pattern rendering enhancement result, and the accuracy of an output image is ensured by simulating a cognitive process formed by layering patterns and integrating cultural implied meaning description and process physical characteristics at the same time; a four-level parallel heterogeneous model is adopted as a discriminator model, a multi-level identification system is constructed, and a generated image is evaluated from four dimensions of pixel authenticity, pattern structure rationality, image and text culture semantic consistency and process feature accuracy, so that high fidelity of an enhanced result is ensured.

The application relates to the technical field of electronic commerce, and discloses a SaaS template intelligent generation and adaptation method for a payment scene. The method first acquires a target payment channel operation sequence and a cross-currency exchange rate, calculates a comprehensive channel health degree and an exchange rate fluctuation rate to construct a multi-dimensional state feature vector; secondly, a symmetric semi-positive definite component interference matrix updated offline is extracted, the feature vector is mapped into a benchmark prediction probability, and multi-dimensional feature cross coupling is combined to calculate an expected comprehensive utility value of a candidate template with a non-negative interference penalty term; subsequently, a dynamic strategy exploration temperature clamped by a threshold is calculated by fusing features, and an adaptation template is generated by sampling in combination with the utility value; and finally, actual conversion results are collected, the order amount proportion with a maximum threshold cut-off is taken as a value weighting factor, and a value weighting approximate gradient is used to perform online adaptive closed-loop updating on a conversion matrix. The application effectively quantifies component bottom layer conflicts, and realizes adaptive closed-loop optimization of a payment interface in a high dynamic environment.

The application discloses a new energy automobile electric drive system performance test bench, and relates to the technical field of test equipment, which comprises an inertia simulation disc and an electric drive simulation structure, wherein the inertia simulation disc comprises an inertia disc shaft, circular mounting racks are fixedly installed at the outer sides of both ends of the inertia disc shaft, plane needle bearings are fixedly installed at opposite sides of the two circular mounting racks, support structures are arranged at opposite sides of the two plane needle bearings, the support structures comprise support bases and upper clamping boxes, and maintenance assemblies are arranged in the upper clamping boxes; the separable design of the upper clamping boxes and the support bases increases the positioning speed of the inertia simulation disc, the inertia simulation disc is quickly positioned and installed with the two support structures and the electric drive simulation structure, the inertia simulation disc can be pre-assembled by the staff, there is sufficient space for assembling the inertia simulation disc, the symmetrical arrangement of the flywheel on the inertia disc shaft is ensured to be completed, and the design rigor of the inertia simulation disc structure is improved.

This invention discloses a learning-based fault-tolerant control method and system for quantifiable performance of nonlinear systems, belonging to the field of automatic control technology. The method designs a learning-based fault-tolerant control algorithm that embeds an RBF network to compensate for fault dynamics when a fault occurs. Based on deterministic learning theory, an RBF network is constructed by setting neurons along a desired reference trajectory. Secondly, by analyzing the convergence characteristics of the learning-tolerant control system through sampled data, a detailed quantitative analysis of the learning accuracy and learning speed of the proposed learning-based fault-tolerant control method is performed, and calculation formulas for learning accuracy and learning speed are given. This invention establishes quantitative expressions for learning speed and learning accuracy through theoretical derivation, realizing quantitative analysis and pre-setting of fault-tolerant control performance, and achieving quantitative controllability of learning speed and approximation accuracy while ensuring the closed-loop stability of the system.

The application provides an acceleration method, system, device and storage medium for quantization speculation sampling, which comprises the following steps: obtaining context content input in a natural language generation task; outputting a candidate sequence in a drafting model of quantization speculation sampling according to the context content; extracting entropy fluctuation features and instantaneous entropy difference features of the candidate sequence, judging the difficulty of task generation of the candidate sequence based on the entropy fluctuation features and the instantaneous entropy difference features, routing the candidate sequence as a text sequence to be verified to a target model with different precisions according to the difficulty, and enabling the target model with a selected precision to perform parallel verification on a predetermined number of text sequences determined. The application realizes a substantial optimization of inference efficiency and memory occupation without significantly sacrificing generation quality.

The invention discloses a method for realizing system hotspot account processing. The method comprises the following steps: receiving a transaction request for a target account; counting the access frequency, and dynamically identifying whether the target account is a hotspot account or not; when the target account is identified as a hotspot account, executing an atomic accumulation operation on a balance change increment value corresponding to the target account in the distributed cache, performing real-time balance verification based on an accumulation result and a pre-stored account reference balance, and returning a transaction processing success response after the verification is passed; the method comprises the following steps of: atomizing and acquiring an accumulated change increment value of each hotspot account from a distributed cache through a timed scheduling task, clearing the accumulated change increment value, and generating a batch updating instruction based on the acquired accumulated change increment value; and executing the batch update instruction in the database transaction. The computing load of high-frequency transactions is transferred from a database to a high-performance memory, so that the transaction processing capacity of the system is improved by magnitude, the response delay is reduced from the second level to the millisecond level, and the high-concurrency real-time scene is met.

The invention relates to the technical field of student learning state monitoring, in particular to a student learning state intelligent monitoring method and system based on behavior analysis, and the method comprises the steps: a data collection unit obtains a glancing path sequence and glancing drop point coordinates of a student in real time through eye movement tracking equipment; the glancing judgment unit constructs a glancing feature judgment model, dynamically optimizes an angle deviation accumulated value threshold value, strengthens abnormal steering contribution in combination with a direction weight factor, and distinguishes target glancing and roaming glancing through speed fluctuation dual-threshold secondary verification of a critical interval; the region matching unit generates a keyword region through natural language processing and a visual saliency model, quickly calculates an Euclidean distance based on R tree index and coordinate normalization, maps the Euclidean distance into a matching degree score and divides a high matching region and a low matching region; and the state decision-making unit outputs a concentration state through a quaternary matrix, continuous N times of targeted glancing and a high matching area, accurately monitors a learning state, and provides a reliable basis for teaching intervention.

This invention relates to a method, apparatus, device, and medium for suppressing non-Ising terms in an NV-center Ising machine. The NV-center Ising machine includes an NV-center system with at least two NV-centers. The method includes: applying a pulse sequence to the NV-center system during the magnetic dipole coupling evolution period to suppress non-Ising terms in the Hamiltonian of the NV-center Ising machine. The pulse sequence is configured to utilize the difference in evolution symmetry between the Ising and non-Ising terms in the Hamiltonian under pulse action, causing the non-Ising terms to cancel each other out over time while the Ising terms are retained. This invention achieves selective suppression of non-Ising terms and retention of Ising terms without increasing hardware complexity, ensuring the rigor of the Hamiltonian form, avoiding ground-state configuration flips caused by non-Ising terms, and significantly improving the computational accuracy of the NV-center Ising machine.

This invention relates to the field of computer vision technology and discloses an AI-synthesized video detection method and system based on multi-agent collaboration. The method includes: acquiring the video to be detected and sampling keyframes; understanding the keyframes based on a visual language model and generating a forgery hypothesis for the current round based on the generated global semantic context; generating a spatial-temporal routing query; performing target localization and segmentation on the video to be detected based on the spatial-temporal routing query; extracting structured physical evidence from the target region video; performing evidence-constrained reasoning to obtain a preliminary judgment result and confidence level; performing consistency checks on the execution trajectory to obtain a reliability score and feedback information, and outputting the final authenticity judgment result. This invention improves the reliability, generalization ability, and traceability of AI-synthesized video detection by combining contextual modeling, hypothesis-driven routing, multi-dimensional physical evidence collection, evidence-constrained reasoning, and closed-loop reflective verification.

The utility model discloses a breaker electrifying mechanism, which comprises a vertical plate, one side of the plate surface of the vertical plate is horizontally provided with a placing plate, the vertical plate is slidably connected with a mounting plate and a driving piece for driving the mounting plate to lift, the mounting plate is provided with an elastic abutting assembly matched with a breaker, and the elastic abutting assembly is provided with a clamping groove. The elastic abutting assembly comprises insulating plates connected with the mounting plate, the number of the insulating plates is consistent with that of wiring ports of the circuit breaker, the width of each insulating plate is smaller than that of the wiring ports of the circuit breaker, the insulating plates are in threaded connection with ball screws, screw bodies of the ball screws are connected with wires, and the wires are connected with the mounting plate. A ball of the ball screw abuts against a wiring board of the circuit breaker. The device can be accurately contacted with the bolt fixing surface of the circuit breaker wiring board, the detection preciseness is ensured, the area of the bolt fixing surface is far larger than that of the upper end surface of the wiring board, the risk of poor contact caused by deviation is reduced, and the detection stability is improved.

Embodiments of the present application disclose a training sample generation method and a corresponding device. The method comprises: obtaining original question and answer data, the original question and answer data comprising query text, document data and first reply data, the document data comprising at least one reference document retrieved based on the query text and used to generate the first reply data, and the first reply data comprising conclusion data; calling a second large language model to analyze a corresponding relationship between the conclusion data in the first reply data and a target reference document in the reference document; calling a third large language model to obtain metadata of the target reference document, the metadata being used to indicate authoritative information of the target reference document; calling a fourth large language model to generate second reply data based on the first reply data, the corresponding relationship and the authoritative information of the target reference document; and generating a training sample based on the query text and the second reply data to train a question and answer model. The scheme can effectively improve the efficiency and quality of generating training samples.

The invention relates to the technical field of computer-aided teaching, discloses a piano music expression teaching method and system based on emotion calculation, remarkably improves scientificity and effectiveness of piano music emotion expression teaching, effectively solves the problem that art intentions are difficult to quantitatively teach in traditional teaching, and improves the teaching efficiency. By constructing a music semantic association network fused with music theory logic, the system breaks through a semantic gap between an abstract music text and a specific acoustic signal, realizes accurate mapping from a recessive emotional artistic conception to a dominant playing technique, and utilizes a cross-modal joint semantic space and a reverse parameter analysis technology to realize accurate mapping of the music semantic association network. According to an emotion background of a target track, a high-dimensional artistic concept can be automatically decoupled into executable physical control parameters such as key touch force and time value deviation, and personalized guidance with clear operation directivity is provided for students.

The utility model belongs to test equipment manufacturing technical field especially, and is a kind of measuring device for the measurement of limit switch action stroke, including base, still including body and micrometer, the micrometer is fixedly connected with the outer wall of base by two screws, the outer wall of micrometer is equipped with two mounting holes for screw placement, the outer wall of base is equipped with two thread blind holes matched with screw, the outer wall of body is equipped with counterbore for installing base and micrometer, the outer wall of body is equipped with the thread hole of installing measured product.The utility model adopts split type structure, and the action stroke of limit switch can be accurately measured by high-precision standard measuring tool micrometer, and it is light and compact in structure, easy to install, and ensures the rigor of measurement.

The invention provides an assembling mechanism and method for an over-constrained hinge, the assembling mechanism comprises a U-shaped sliding frame, the front end and the rear end of the U-shaped sliding frame are each provided with a hollow limiting barrel, a to-be-assembled hinge shaft penetrates through a to-be-assembled shaft hole of a hinge body, and the two ends of the to-be-assembled hinge shaft are inserted into the two limiting barrels correspondingly; the hinge shaft and the hinge body are driven by the U-shaped sliding frame to move synchronously, so that the hinge shaft to be assembled and the reference hinge hole are coaxially arranged, and the assembling position of the hinge shaft to be assembled is determined. The U-shaped sliding frame is borne by a rectangular hollow box body, a lead screw is arranged in the rectangular hollow box body, the lead screw can drive a baffle to horizontally move in the left-right direction when rotating, then the baffle pushes the U-shaped sliding frame to move, a cylinder is welded to the bottom of the rectangular hollow box body downwards, the cylinder is directly connected to a stud of a rack in a sleeving mode, and a lifting nut is installed on the stud. The lower end opening of the cylinder is pressed on the upper end face of the lifting nut, so that the rectangular hollow box is lifted by rotating the lifting nut.