39results about How to "Valid response" patented technology

The invention discloses an asset risk tracing method and device. According to the method, the network topological graph and the asset vulnerability list are obtained, the system asset topological graph is drawn to identify the key asset risk, and the system risk list is formed. And further drawing a data flow diagram, identifying data asset risks, and forming a data risk list. Big data analysis is used for identifying risk events and influences thereof, a risk event causal chain is constructed, and risk roots are traced. And based on the risk source, constructing a risk propagation map, and realizing visualization and dynamic tracking of the risk event.

The invention discloses a microencapsulation repairing agent and an intelligent self-repairing ultrahigh-strength ultrahigh-toughness cement-based structural material, the microencapsulation repairing agent is mainly composed of a humidity-responsive outer layer, a pH-responsive middle layer and a temperature-responsive inner layer, and the outer layer is modified with a silane coupling agent. The intelligent self-repairing ultrahigh-strength ultrahigh-toughness cement-based structural material is mainly prepared from the microencapsulated repairing agent, nano carbon black, nano montmorillonite, nano cellulose and other raw materials. According to the invention, by introducing the self-repairing microcapsule with a specific structure and materials such as nano carbon black, nano montmorillonite and nano cellulose, the strength, toughness and durability of the concrete are remarkably improved, and the concrete has an intelligent self-repairing function.

The invention discloses an industrial internet security situation assessment system based on deep learning, and relates to the technical field of industrial internet security, which comprises a data acquisition module, a data preprocessing module, a feature extraction module, a deep learning model training module and a data storage module, the system has the advantages that the deep learning model training module adopts a combined architecture and an optimization algorithm to train an accurate model, the real-time monitoring module monitors real-time data in the industrial internet according to received data, abnormal conditions are found in time, and the real-time monitoring module monitors the real-time data in the industrial internet according to the real-time data. The method comprises the following steps of: acquiring the security situation value data of the current industrial internet, transmitting the security situation value data of the current industrial internet to a situation awareness module, and performing deep quantitative evaluation and trend prediction by the situation awareness module by using a fuzzy logic and evidence theory fusion algorithm and integrating historical and real-time data to accurately calculate a comprehensive security situation value so as to calculate a more accurate comprehensive security situation value. And accurate judgment and timely and effective response to the security situation are ensured.

The invention discloses a Beidou-based slope monitoring and early warning system evaluation method, particularly relates to the technical field of system monitoring, and is used for solving the problem that a fault of an existing slope monitoring and early warning system is not found in time. Analyzing a time synchronization function of the Beidou system to realize data synchronization between the target sensors and analyzing automatic calibration conditions of the target sensors; on the basis that the data synchronism is normal and the sensor is reliable to use, the consistency of data fusion is further analyzed through an entropy theory, vibration influence evaluation and adaptability evaluation caused by a vehicle are analyzed, key monitoring is conducted for a high-risk time period, and through comprehensive analysis, the accuracy of data fusion is improved. The system can generate detailed early warning information for a specific monitoring scene, the safety of slope monitoring and the accuracy of early warning are enhanced, the data processing efficiency is improved through the staged processing flow, and disasters and accidents caused by inaccurate data or improper analysis are effectively prevented.

The invention discloses a network intrusion detection method based on multi-task deep learning, and the method comprises the steps: obtaining an intrusion detection data set, carrying out the mapping and one-hot coding of attack class labels of the intrusion detection data set, and obtaining the features of the intrusion detection data set; preprocessing the intrusion detection data set features to obtain a preprocessed intrusion detection data set; constructing a multi-task learning model based on hard sharing, and inputting the preprocessed intrusion detection data set into the multi-task learning model based on hard sharing for training to obtain a trained multi-task learning model based on hard sharing; and obtaining a target intrusion detection data set, inputting the trained hard sharing-based multi-task learning model for detection, and obtaining a detection result of the intrusion network. According to the method, through knowledge sharing among different tasks, the detection accuracy can be obviously optimized, and various network attacks can be effectively identified and responded.

The present invention discloses a network attack early warning and tracing method, system and device based on a knowledge graph of facts, obtains network attack records to build a knowledge graph layer; extracts event causal relationships from network attack records, forms attack links, and aggregates and generalizes events and causal relationships to build a graph layer of facts; maps generalized nodes in the attack link with knowledge graph layer entities to establish a network attack knowledge graph of facts; infers the attack means taken by the attacker, or predicts the attack means to be taken in the next step, thereby realizing the tracing and early warning of the attack behavior. The present invention combines the facts graph and knowledge graph technology, and through the construction of the facts graph layer and the knowledge graph layer, transforms the network attack link and the organizational information asset architecture into a reasoning graph that combines dynamic facts logic with static objective knowledge, and realizes the reasoning and prediction of the overall attack behavior based on a small amount of exposed attack traces, so as to support the rapid and effective response of network attacks.

The invention discloses a micro-service chaos test method and device based on Istio and link tracking, and relates to the technical field of cloud native, and the method comprises the steps: S1, submitting a test task; s2, initializing a test environment; s3, tracking a micro-service-level calling link of the request through a link tracking function, and generating a request tracking tree in combination with the request definition and the micro-service-level calling link; s4, implementing a bottom-up test strategy: starting to implement test cases from bottom to top from a leaf node of the request tracking tree, wherein the execution of a single test case comprises the steps of injecting a candidate fault, initiating a specified request, and triggering an Envoy filter to obtain a preset response; and S5, generating a final test result. Generation and execution of the test cases are automatically completed by the system, complexity and labor intensity of manual operation are greatly reduced, and efficient tracking data acquisition and processing are achieved.

The invention discloses a potential risk hidden danger identification method and device based on multi-dimensional information and event causal sorting, equipment, a medium and a product, and relates to the field of artificial intelligence. The method comprises the following steps: acquiring multi-modal data from a subscribed public opinion monitoring object, performing feature extraction, and extracting multi-modal information features; performing data structured analysis based on the multi-modal information features, and extracting key attribute structured data of each event; performing clustering analysis on all the events, and dividing all the events into a series of large event sets; performing information deduplication and integration analysis on each small event in the large event set to obtain key attribute structured data of each large event set, performing causal chain sorting on an occurrence sequence and a causal relationship of a series of large event sets to obtain an event causal chain, and performing potential risk hidden danger identification on the event to obtain a hidden danger identification result. The comprehensiveness and timeliness of public opinion monitoring and the accuracy of public opinion analysis can be improved.

The invention discloses a floating type photovoltaic platform capable of actively absorbing waves. The floating type photovoltaic platform comprises a platform floating body and an active wave absorbing device, the platform floating body comprises a plurality of platform buoys, and the platform buoys are connected through flexible connecting pieces; the active wave absorbing device is connected with the platform floating body; the active wave absorbing device comprises an active wave absorbing plate, an active wave absorbing cabin floating body and a propelling rod; a radar wave measurement sensor is arranged on the active wave absorbing cabin floating body, and a control module is arranged in the active wave absorbing cabin floating body; one end of the propelling rod is connected with the active wave-absorbing cabin floating body, and the other end of the propelling rod is connected with the active wave-absorbing plate; the control module controls the pushing rod to stretch out and draw back according to data of the radar wave measurement sensor, the active wave absorbing plate is driven to move, the technical problems that the sea environment wave condition is poor, and the wave resisting effect of the floating type photovoltaic platform is poor are solved, and the structural strength and stability of the whole platform are enhanced.

According to the self-adaptive soft rock slope anchor rod supporting system and the calibration method thereof, deformation of a soft rock slope is effectively adapted through relative sliding of a built-in compression spring and a wear-resistant steel plate. When the soil body expands or deforms, the compression spring is compressed, and the second wear-resistant steel plate in the pedestal assembly slides outwards along the first wear-resistant steel plate, so that the pedestal moves towards the outer side of the soil body, and the deformation pressure is released. And when the soil body shrinks, the compression spring recovers, the second wear-resisting steel plate slides inwards, the pedestal moves towards the inner side of the soil body, the anchor rod retracts, and effective supporting on the slope is kept. According to the mechanism, the adaptability and the supporting effect of the anchor rod supporting system are improved, and the stability of the soft rock slope is enhanced. The calibration method based on the sensor unit ensures the lasting reliability of anchor rod axial force monitoring and the overall safety of an engineering project, and provides advanced technical support for stable control of a soft rock slope.

The invention relates to the technical field of environment management, and discloses an eco-friendly urban environment design implementation method, which comprises the following steps: S1, constructing a distributed clean energy system: realizing local energy production, storage and allocation through micro-grid and regional collaboration; s2, establishing an environment monitoring and response system: acquiring data through a sensor network, and implementing hierarchical response; s3, resource demand prediction and scheduling are realized: resource demands are predicted by using a dynamic model, and multi-level scheduling optimization is carried out; s4, establishing an ecological building and community treatment system: intelligently regulating and controlling the temperature and humidity of the building, and constructing a community water resource circulation system; and S5, designing a public participation incentive platform: providing an incentive mechanism to encourage environmental protection behaviors. Through the distributed clean energy management system, localized production, storage and flexible allocation of energy are realized, and meanwhile, the energy is intelligently scheduled by adopting an optimization algorithm, so that the supply and demand balance of the energy is realized, and the utilization rate of the clean energy is improved.

The application relates to the technical field of aerial video analysis, and discloses a large-scene multi-modal analysis system and method based on a UAV. The method acquires an original video frame sequence from aerial equipment, extracts a scene change period and an object motion trend by calculating an inter-frame motion feature vector, and judges whether a scene is in a stable or dynamic state by means of a state classification model. In the dynamic state, a tracking target position is calculated according to preset parameters, and an analysis target area is adjusted in combination with the motion trend; a camera parameter adjustment instruction is generated according to a deviation amount of the analysis target area from an actual object position, and is output to an executing mechanism; a complexity value is acquired through a scene complexity feedback signal, and when the complexity value exceeds a preset range, an adaptive algorithm is used to update an analysis strategy and output an adjustment signal; the output timing of control and strategy adjustment signals is optimized, the frame sequence and analysis parameter change trend are monitored in real time, preset parameters are dynamically updated to match user requirements, and efficient video analysis processing is realized.

The invention provides a power business interaction session processing method and system based on a large language model. The method comprises the following steps: firstly, obtaining a session semantic understanding vector sequence of a target power business interaction session record; and then semantic enhancement processing is carried out on the session semantic enhancement vector sequence to obtain a session semantic enhancement vector sequence. And finally, the reinforcement vector sequence is loaded into a first session record annotation network which is generated through network parameter learning according to a session semantic extraction instruction and a theme induction instruction, the loading data of the first session record annotation network is a first sample learning session record sequence, and the loading data of the first session record annotation network is a second sample learning session record sequence. The sequence comprises a first sample session semantic understanding vector sequence subjected to enhancement processing and subject induction distribution thereof. Through the mode, the session record annotation data of the target electric power business interaction session record can be generated, so that accurate analysis and processing of the electric power business interaction session are realized, the quality and efficiency of electric power services are improved, and the requirements of users on the aspect of electric power businesses are better met.

The invention relates to the technical field of risk early warning, in particular to a coal mining risk early warning system based on data processing, and the system comprises a dividing module which divides a to-be-mined area based on a preset dividing standard; the data acquisition module is used for acquiring a plurality of real-time geological data and a plurality of real-time environment data corresponding to a plurality of to-be-mined point locations in real time based on a preset frequency; the data processing module is used for calculating geological safety based on a plurality of real-time geological data corresponding to any mining point, calculating environment mining safety based on a plurality of real-time environment data corresponding to any mining point, and calculating actual mining safety corresponding to any mining point based on the geological safety, the environment mining safety and a preset weight; and the strategy generation module gives an alarm based on a comparison result of a plurality of actual mining safety corresponding to the plurality of to-be-mined point locations and preset safety, or adjusts a preset division standard, or adjusts a preset frequency. According to the invention, the accuracy of coal mining safety early warning is improved.

The present application relates to the technical field of three-dimensional image data processing, and particularly relates to a preoperative auxiliary planning MRI image laryngeal tumor three-dimensional reconstruction system. For each voxel point in the initial three-dimensional model of the larynx, the system constructs a preoperative three-dimensional laryngeal image result through tissue image features. In the intraoperative stage, the expected tissue change characteristics are obtained according to the information of the instrument coordinate trajectory in the three-dimensional laryngeal image structure, and compared with the actual tissue change characteristics embodied by the power feedback data sequence of the electrocautery, so as to determine the abnormal type of the tissue under the coordinate trajectory, and update the labeling in the initial three-dimensional model. The present application can effectively identify the abnormal type of the detailed tissue feature area by comparing the expected tissue change characteristics with the actual tissue change characteristics, and then update and render the three-dimensional model in real time through the labeling method, so as to realize the effective response of the intraoperative characteristics.

The application discloses a method for interactive multi-model adaptive vibration active control based on variational Bayes, and relates to the technical field of vibration control, comprising the following steps: a system model set containing multiple potential dynamic modes is established, and initialization setting is performed on each model; in each control sampling period, variational Bayes iteration is performed on each model; the above process is repeated for each channel to obtain optimal state estimation of each channel; covariance cross fusion method is used to fuse the state estimation results of multiple channels to calculate global optimal state estimation; the global optimal state estimation is convolved with a reference signal filtered by a secondary channel model to generate a reverse control signal, the reverse control signal is driven by a power amplifier to drive an actuator to generate a secondary force to offset the original vibration, and vibration suppression is realized. The application realizes high-precision and high-robustness vibration suppression by fusing variational Bayes adaptive Kalman filtering and interactive multi-model estimation.

The present invention relates to the field of smart grid security access, and provides a smart grid security access control method, system and terminal device. The smart grid security access control method includes, according to the performance indicator data and network flow data of key equipment in the access process and all access behaviors of the access network equipment, respectively calculating the trust values ​​corresponding to the performance indicators, network flow and access behaviors of the access network equipment; based on the trust values ​​corresponding to the performance indicators, network flow and access behaviors of the access network equipment, and comparing them with their respective corresponding thresholds, determining the performance indicator authorization level, network flow authorization level and access behavior authorization level; respectively screening out the lowest level among the performance indicator authorization level, network flow authorization level and access behavior authorization level, and using it as the final authorization level of the access network equipment to determine the access scope. The present invention can timely discover and effectively respond to the evolution of security threats.

The invention relates to the field of automobiles, in particular to a battery overcurrent protection method and related equipment. The method comprises the following steps: acquiring a plurality of different over-current thresholds and a current signal of a target battery; wherein different over-current threshold values correspond to different judgment durations; the higher the overcurrent threshold is, the shorter the corresponding judgment duration is; and when the time that the current signal continuously exceeds any overcurrent threshold reaches the corresponding judgment duration, performing overcurrent protection on the target battery.

A full-size medium-length highway tunnel fire experiment emergency management and control method based on a mixed display technology comprises the steps that a plurality of professional groups are divided, then all the professional groups are arranged in corresponding positions of a full-size medium-length tunnel fire experiment platform, when a tunnel fire experiment is carried out, all the professional groups are responsible for different responsibilities, and all the professional groups are responsible for different responsibilities. When a tunnel fire experiment exceeds a normal experiment range and fire extinguishing cannot be carried out, the fire experiment and emergency disposal group receives emergency disposal information issued by the monitoring center group and carries out field emergency disposal according to the information. Meanwhile, the field machine group, the medical aid group, the safety evacuation group, the fire-fighting contact group and the fire-fighting group carry out corresponding operation according to the emergency disposal information, finally, the logistics and comprehensive coordination group carries out tunnel inspection and cleaning after a disaster, and the monitoring center group collects and records related data of a tunnel fire test. Reliable data basis is provided for practical engineering application, so that loss is reduced to the maximum extent, and life and property safety is protected.

The application relates to a business data processing system, method, storage medium and equipment. The system comprises a business operation layer and an object aggregation layer which are independent of each other, and the business operation layer and the object aggregation layer transmit data in an asynchronous decoupling mode. The business operation layer performs a persistent operation on original business data to form persistent business data, and stores the persistent business data in a database. The object aggregation layer processes data of multiple business operation scenes according to a user business request to form aggregation data, and sends the aggregation data as a first response result to a user terminal. The data of the multiple business operation scenes comprises the persistent business data. The application can more quickly and effectively respond to business logic, can support efficient business application in complex, changeable and extended scenes, reduce the bloated, uncontrollable and unsustainable of a lightweight architecture system after continuous iteration, and maintain the lightweight architecture and flexibility of the business system.

The application relates to the field of network security monitoring, and discloses a method and system for picture and video retrieval, which are characterized by the following steps: setting a frame image acquisition module, a picture tracing module, an implantation identification module and an object processing module, performing continuity judgment on image frames of video content, effectively responding to and extracting the content randomly implanted in the video, performing network retrieval on the features of the extracted safety identification image, effectively acquiring the implanted content in the video according to the image features of the source image, and judging the network security of the related implanted content. Compared with the traditional method, the method is more efficient and reliable, and has higher implanted content identification effect.

The invention provides a server exception handling method, which comprises the following steps of: monitoring the running state of a server in real time, and judging whether the server is in an exception state or not through a set monitoring index; when detecting that the server is abnormal, recording abnormal information and generating an abnormal report; executing a corresponding processing strategy according to the exception type; and after the processing is completed, checking the state of the server to ensure that the server recovers normal operation, and recording the exception processing process in a log. Potential problems can be found in advance through a multi-level monitoring and early warning mechanism, and measures can be taken before an exception occurs through an automatic processing mechanism, so that deterioration of the problems is prevented. Through the functions of recording detailed logs and notifying a system administrator in the exception detection and processing process, the management convenience is improved, and the administrator can know the system condition in time and carry out subsequent optimization. The comprehensive early warning and automatic processing mechanism further reduces the demand of manual intervention, and improves the operation and maintenance efficiency.

The invention discloses a Pd modification-based SnO2 hydrogen sensor sensitive material preparation method, which comprises: dissolving stannous chloride dihydrate and polyvinylpyrrolidone in a solvent according to a certain ratio to obtain a uniform mixed solution; carrying out solvothermal reaction, washing, drying and calcining treatment on the mixed solution to prepare pure SnO2 nano powder; and ultrasonically dispersing the prepared nano SnO2 powder in ethanol, adding a PdCl2 solution, uniformly dispersing, drying, and calcining at high temperature, thereby obtaining the catalyst. The hydrogen sensor sensitive material has good response to low-concentration hydrogen and can be used for leakage detection of low-concentration hydrogen.

The invention belongs to the technical field of power grid energy storage management, and particularly relates to an electrochemical energy storage management method and system for a micro-grid, a terminal and a storage medium, and the method comprises the steps: obtaining the real-time multi-dimensional data of the micro-grid through a plurality of sensors disposed in the micro-grid, and transmitting the obtained multi-dimensional data to a data processing center through a communication module; the obtained multi-dimensional data provides a comprehensive and accurate information basis for load prediction, and the load prediction model constructed by using the machine learning algorithm can accurately predict the energy demand in the future preset time period based on the real-time data, thereby guiding the charging and discharging strategy of the electrochemical energy storage system, and improving the performance of the electrochemical energy storage system. And the accuracy and the real-time performance of energy storage and scheduling are obviously improved.

This invention provides a non-contact interactive system based on a photoelectric sensor array, comprising: a photoelectric sensor array, the photoelectric sensor array including: a transparent substrate; a conductive layer formed on the transparent substrate; a patterned confinement layer formed on the conductive layer for forming a patterned array of photoelectric active materials; a patterned array of photoelectric active materials formed on the patterned confinement layer, wherein each patterned unit in the array forms a miniature photoelectric sensor unit under the drive of an external bias voltage; a surface light source located on the back side of the substrate of the photoelectric sensor array; and a reflector movably located on the front side of the substrate of the photoelectric sensor array. This interactive system utilizes the high responsivity and fast response speed characteristics of the photoelectric sensor array to enable the interactive interface to quickly track signals from moving objects, and achieves photocurrent growth through light reflection from the reflector onto the surface light source, thereby realizing a responsive, contactless, three-dimensional human-computer interaction.

The invention relates to the technical field of power electronics, in particular to a safety inverter with double protection mechanisms, which comprises an inverter body and a heat dissipation device, the heat dissipation device comprises a shell and a cooling pipe arranged in the shell, a gas tank used for filling fire extinguishing gas is arranged on the outer side of the shell, and the outer side of the gas tank is provided with a gas outlet. The air tank is communicated with an air pipe which penetrates through the inverter body and extends into the air tank, an opening and closing assembly is arranged at the joint where the air pipe is communicated with the air tank, a linkage assembly used for automatically opening the opening and closing assembly under the condition of spontaneous combustion in the inverter body is arranged between the cooling pipe and the air tank in a matched mode, and a smoke sensor is arranged on the inverter body. Heat generated in the inverter body is effectively absorbed and dissipated through the cooling liquid circularly flowing in the cooling pipe, and when spontaneous combustion occurs in the inverter, the opening and closing assembly is rapidly opened by using the cooling liquid as a power source, so that inert gas in the gas tank is rapidly sprayed into the inverter, and the combustion reaction is effectively inhibited.

The invention belongs to the technical field of energy power data security, and particularly relates to an intelligent question-answering system and method in the field of power data security based on community detection. Comprising a large language model module, a knowledge reasoning module, a data security management module and a database module. The large language model module is used for analyzing semantics of problems; the knowledge reasoning module is used for performing knowledge reasoning on the semantics of the question and generating an answer; the data security management module comprises a data encryption module, an identity authentication module, an authority control module and an audit tracking module; the database module comprises an energy power basic data sub-library, an equipment operation data sub-library, a historical question and answer record sub-library and a user behavior data sub-library; in the electric power data security analysis process, the big language model technology and professional knowledge reasoning are combined, automatic question answering of the electric power data security problem is achieved, electric power workers are assisted in rapidly obtaining needed information, the decision-making efficiency is improved, and manual operation errors are reduced.

The invention discloses an interface fault tolerance improving method applied to an urban operation center platform, and relates to the technical field of computer Java back-end development. Comprising the steps of 1, defining an interface or a method needing to be intercepted by using a tangent point expression by using a section-oriented programming (AOP) method, and intercepting calling of the interface in a central platform system according to the interface needing to be intercepted, 2, capturing any thrown exception in the interface calling process, recording an exception log for subsequent analysis when the exception is captured, 3, according to the captured abnormal interface name, a pre-cached preparation result is matched and queried in the cache, and 4, a query result is returned to a user of the central platform system.

The invention relates to the technical field of public health, in particular to a campus public health management system, which comprises a collection module used for collecting case information uploaded by a user; a storage module; the statistical module is used for counting the number of diseases in the range from the first N days to the today; the analysis module is used for extracting an itinerary record from the corresponding case information when the counted number of diseases exceeds an early warning threshold value, and analyzing whether places or items which appear repeatedly for several times exist in the itinerary record or not; and the matching module is used for matching a corresponding prevention and control scheme according to the disease when a plurality of repeated places or items exist, and sending the prevention and control scheme to a person in charge of the plurality of repeated places or items. According to the invention, effective response and prevention and control are carried out by overall planning of case information in the school, the risk of disease infection is reduced, and the management of public health in the school is facilitated.