16results about How to "Highly systematic" patented technology

The invention provides a PQC and SM2 / 9 cooperative operation cryptographic chip and method based on an RISC-V architecture, and belongs to the technical field of cryptographic security. The chip comprises an RISC-V core and a configurable password collaborative operation unit, wherein the configurable password collaborative operation unit comprises a collaborative control state machine and a unified operation unit capable of being dynamically reconfigured. The method comprises the following steps: receiving and decoding a single cooperative operation instruction from an RISC-V core through a cooperative control state machine, and obtaining operation data feature information; the data length and the security level identification are extracted, and the optimal collaborative operation process is selected in a self-adaptive mode through comparison with a preset threshold value; and finally, dynamically configuring and scheduling a unified operation unit according to the selected process, and completing cooperative operation of the post-quantum cryptography algorithm and the SM2 / SM9 algorithm in an atomization mode. According to the method, deep fusion and intelligent scheduling of the two algorithms are realized on the hardware level, and the efficiency, the resource utilization rate and the safety of cooperative operation are improved.

The invention discloses a simulation method and device of an AR optical system, a medium and electronic equipment, and the method comprises the steps: obtaining an initial source file, converting the initial source file into a target file based on a Kogelnik coupling wave theory and a preset volume holographic grating structure requirement, and importing the target file into ZEMAX; acquiring a corresponding luminous source according to preset parameters of the display; obtaining an initial collimation component, converting the initial collimation component into a target collimation component, and importing the target collimation component into the ZEMAX; in a non-sequence mode of ZEMAX, calling a target file, generating a volume holographic grating, and obtaining a holographic waveguide assembly; and connecting the light emitting source, the target collimation assembly, the holographic waveguide assembly and a preset detector to obtain the target AR optical system. Compared with the prior art, simulation of the holographic waveguide assembly and simulation of the integrity of the AR optical system can be achieved, the simulation efficiency is improved, the systematicness, integrity and quality of simulation are improved, and then the optical performance of the optical system in AR equipment is improved.

This invention relates to the field of expected functional safety testing technology for autonomous vehicles, specifically to an accident scenario screening and matching device and method for SOTIF testing requirements. The device includes a processing system comprising an acquisition module, an analysis module, a risk modeling module, and a matching module. The risk modeling module uses Fault Tree Analysis (FTA) to perform a structured decomposition of SOTIF risk causative factors, quantifies the importance of risk elements through a combination of subjective and objective weighting, and outputs a comprehensive weight for each risk element. The matching module combines the comprehensive weight of risk elements to weight and enhance the accident scenario text, filtering out accident scenarios that match the test requirement text. This invention achieves precise matching between test requirements and accident scenarios by semantically associating risk elements with accident scenario text in an accident database.

The application discloses an automatic driving scene generation method and device and a vehicle, and relates to the technical field of automatic driving scene generation, and in particular to a method for generating a scene by using a world model, a long-tail safe scene, risk attribution analysis, counterfactual reasoning, and multi-objective comprehensive scoring and iterative re-determination screening.

This application provides a geological disaster safety risk assessment method based on rainfall, landslides, and transmission tower deformation, relating to the field of geological disaster prediction. The method includes: collecting multi-source data in the slope area where the transmission tower is located; constructing a rainfall-induced soil moisture content response model and dynamically correcting the soil shear strength parameters; calculating the landslide stability safety factor based on the corrected soil shear strength parameters; constructing a comprehensive deformation index for the transmission tower; obtaining a rainfall risk index; and combining the landslide stability safety factor and the comprehensive deformation index of the transmission tower to construct a comprehensive risk assessment model, outputting the risk level and early warning signal. This application constructs a dynamically coupled risk assessment model of the three elements of "rainfall-slope-tower," realizing a comprehensive analysis from meteorological disaster to structural response.

This invention provides a method for digital modeling and visualization of plant transpiration processes, comprising: firstly, setting corresponding data acquisition nodes in each plant zone to collect air humidity, transpiration water volume, and root zone soil pressure values, and generating a transpiration monitoring data sequence; then, calculating the transpiration rate and percentage change in transpiration based on the transpiration monitoring data sequence to construct a dynamic parameter set for transpiration; further, constructing a digital model of plant transpiration based on the dynamic parameter set for transpiration, and optimizing the model weight parameters using reinforcement learning to generate a predicted value for transpiration intensity; subsequently, generating a sequence of transpiration image frames based on the predicted value for transpiration intensity to achieve dynamic visualization of the transpiration process; finally, synchronizing the transpiration image frame sequences of different plant zones in time, calculating the difference in transpiration intensity, and generating a comparative visualization demonstration result of the plant transpiration process.

The invention discloses a device and a method for detecting interface debonding of a hydraulic concrete structure repaired by FRP, and relates to the field of intelligent operation and maintenance of hydraulic engineering, the device comprises a probe and a host, the probe integrates acoustic detection and piezoelectric ceramic implantation functions, and can strike over the FRP surface and rapidly and preliminarily screen a debonding area through sound signal abnormity, and the probe is used for detecting the interface debonding of the hydraulic concrete structure repaired by the FRP. Precisely implanting a piezoelectric ceramic sensor and a matched curing agent into the debonding part by using the same probe to form a long-term monitoring point; by means of the method, the integrated operation process of rapid initial detection, fixed-point implantation and key detection is achieved. According to the invention, reliable implantation and stable signal acquisition of piezoelectric ceramics are realized, the problem of disjunction between detection of a traditional method and long-term monitoring and later detection is solved, and the device has the advantages of high integration level, capability of long-term fixed-point tracking and high applicability.

This application provides a method and system for enterprise risk assessment based on a large language model and text quantitative analysis. The method includes: acquiring and parsing the current first annual report text of a target enterprise to obtain several subheadings and corresponding subtexts; dividing the subtexts corresponding to each subheading into corresponding semantic chapters using a preset large language model, thereby generating corresponding first reconstructed texts; extracting corresponding first target texts from the first reconstructed texts according to preset target semantic chapters; performing a difference comparison analysis on the first target text and the second target text using the large language model to obtain several difference texts and corresponding several change trends; calculating several analysis indicators based on the number of each difference text, each change trend, and the average number of words in each chapter, and conducting a risk assessment of the target enterprise based on each analysis indicator to generate a risk assessment result, thereby improving the effectiveness and accuracy of the risk assessment.

This application discloses a learning plan updating method and apparatus based on an AI intelligent agent, relating to the field of educational technology. The method includes: responding to acquiring learning behavior data of a student learning questions based on a learning plan in a peer learning system; determining the question information and note information of the student's target questions based on the learning behavior data; determining the set of implicit knowledge points in the knowledge point set corresponding to the question information and note information based on a first set of knowledge points marked for the target questions; determining the target implicit knowledge point set corresponding to the learning plan from the implicit knowledge point set based on the prerequisite and relevance information between the implicit knowledge point set and the first knowledge point set; and updating the target implicit knowledge point set in the knowledge point learning grid corresponding to the learning plan to update the learning plan to a target learning plan including the target implicit knowledge point set. This application can improve learning efficiency and the systematic nature of knowledge construction.

The invention discloses a cryptographic module attack surface assessment method and system based on multi-modal side channel information fusion, and relates to the technical field of cryptographic module attack surface assessment, and the method comprises the steps: constructing a plurality of side channel attack scenes for a to-be-assessed cryptographic module; collecting multi-modal side channel information to form a multi-modal side channel data set, and generating a plurality of side channel attack paths based on the attack condition combination relationship; key indexes are calculated, and a path evaluation result corresponding to the attack path is formed; screening path evaluation results of the side channel attack paths based on an attack feasibility judgment rule, determining an effective attack path set, and counting distribution characteristics of the effective attack paths under different side channel mode combinations and attack condition combinations; based on the effective attack path set and the distribution characteristics, outputting an attack surface evaluation result; the problems that in the prior art, single-mode analysis is one-sided, an attack path cannot be executed or is redundant, and attack face risks are lack of systematic quantification are solved.

The invention discloses a park-level virtual power plant-oriented multi-microgrid hierarchical collaborative optimization scheduling method, and relates to the technical field of microgrid optimization scheduling, and the method comprises the steps: carrying out the multi-source photovoltaic data fusion and high-confidence power generation prediction; carrying out layered progressive load decomposition and demand baseline establishment; carrying out local multi-target self-optimization; real-time coordination of dynamic excitation is realized; micro-grid response and VPP polymerization clearing are carried out; and executing evaluation and model evolution. According to the method, the fundamental problem that a complete and feasible technical solution cannot be provided for the transverse aggregation type park under the condition of lack of physical conditions in the prior art, and efficient, reliable and sustainable resource aggregation cannot be realized is solved.

This invention discloses a carbon-plastic bipolar plate for a zinc-bromine flow battery, its preparation method, and its application, belonging to the field of electrochemical energy storage technology. The method includes: dispersing nitrogen-doped hollow carbon nanotubes and spraying them onto the positive electrode side of a carbon-plastic bipolar plate; after drying, a nitrogen-doped hollow carbon nanotube-modified positive electrode carbon-plastic bipolar plate is obtained; dispersing boron-nitrogen co-doped carbon and spraying it onto the negative electrode side of a pretreated carbon-plastic bipolar plate, after drying again, a boron-nitrogen co-doped carbon-plastic negative electrode carbon-plastic bipolar plate is obtained. On the positive electrode side, the nitrogen-doped hollow carbon nanotubes catalyze the bromine reaction through nitrogen doping, reducing the overpotential; the hollow structure adsorbs bromine species and uses charge action to inhibit bromine permeation, reducing self-discharge. On the negative electrode side, the boron-nitrogen co-doped carbon uses B-N zinc-loving sites to guide uniform and dense zinc deposition, inhibiting dendrite formation; and inhibits hydrogen evolution through charge regulation. Both methods synergistically improve the bromine barrier performance, reaction kinetics, and dendrite suppression ability of the carbon-plastic bipolar plate.

The invention belongs to the technical field of medical simulation training and surgical education, and discloses a urinary surgery training method and system based on augmented reality simulation, electronic equipment and a storage medium. The method comprises the following steps: S1, constructing a virtual operation scene according to a preset three-dimensional anatomical model of the urinary system; s2, integrating a real-time interactive surgical instrument digital twinborn model in the virtual surgical scene; s3, according to a user operation input signal, driving the surgical instrument digital twin model to dynamically respond in the virtual surgical scene; s4, superposing the dynamically responded virtual operation process into a real training environment visual field through augmented reality display equipment; and S5, generating corresponding operation track data according to continuous operation behaviors of the user in the superposed visual field, and storing the operation track data in a training database. According to the method, the defect of scene splitting in traditional virtual reality training can be effectively overcome through high-precision space registration and real-time rendering.

The invention discloses a gene pool central control method and system based on artificial intelligence, and the method comprises the steps: carrying out the real-time monitoring of multi-dimensional parameters through all nodes, judging a risk state, setting a window, judging a same-period risk, extracting cleaning data, carrying out the feature screening, cause verification and refining, and forming a feature set; and constructing a weighted scoring early warning model to realize graded early warning and iterative optimization. According to the scheme, the cross-node generality risk can be accurately identified, the early warning reliability is improved, and stable operation of the gene cold storage cluster is guaranteed.

The application discloses a partial discharge diagnosis method based on regional clustering, which firstly extracts pulse repetitive discharge spectrum data and corresponding labels in a partial discharge training set and stores the data as a mapping matrix. Through a primary clustering function, corresponding selected region coordinate matrices are obtained. The selected region coordinate matrices are classified according to the labels, and the result is stored in a clustering data dictionary. The labels and the selected region coordinate matrices in the clustering data dictionary are iterated, and are sent into a secondary clustering function to obtain final diagnosis region coordinate matrices. Whether the collected PRPD spectrum data to be diagnosed is faulty is judged in combination with a discharge frequency threshold, a corresponding fault occurrence probability is calculated, and finally a partial discharge fault diagnosis result containing the fault occurrence probability is generated.

The invention relates to the technical field of intelligent detection of high-temperature alloys, in particular to an intelligent detection method based on corrosion resistance of high-temperature alloys, which comprises the following steps of: automatically separating an initial corrosion stage from an accelerated corrosion stage by utilizing a time sequence accumulation characteristic of data by acquiring surface state and environmental response data of the high-temperature alloys after multiple cycles in different corrosion environments; and the corrosion environment category is identified according to the disturbance difference of the environment response data in the two stages. By calculating environmental adaptability parameters of an initial stage and integrating associated data of passive film attenuation and medium concentration in an acceleration stage, stage characterization values are generated, and representative samples are screened. Correlating the corrosion depth and film thickness data of all alloys in the acceleration stage, establishing a corrosion behavior transmission map, and finally assigning differentiated detection strategies for different alloys based on the map. According to the method, the dynamic correlation analysis of the corrosion process and the intelligent differentiation making of the detection strategy are realized.