11results about How to "Risk prevention" patented technology

The invention provides a medical data privacy protection method and system based on artificial intelligence, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the feature analysis of medical data, building a scoring matrix, generating a privacy risk assessment result, dividing a security domain, and building a distributed cooperation mechanism through federal learning; preprocessing data at a local node, constructing a deep neural network model, encrypting gradient information by using a dynamic key matrix, and performing distributed aggregation operation and verification; forming a data privacy protection scheme; and performing identity verification and anomaly detection on the access request, and dynamically adjusting the access granularity. According to the method, the security and the flexibility of medical data privacy protection are improved, and meanwhile, the availability of the data is ensured.

The invention relates to the technical field of enterprise cloud management, and discloses an ERP enterprise cloud management system, which comprises a system main body deployed based on a cloud computing architecture, the system main body is integrated with a financial management module, an inventory control module, a purchase management module, a sales management module, a production plan module, a human resource management module and a customer relationship management module, and data interaction interfaces and cooperative work mechanisms are arranged among the modules; data are stored by the cloud storage unit, and a data processing task is executed by the cloud operation unit. The ERP enterprise cloud management system breaks data barriers among departments of an enterprise, integrates core modules of financial management, inventory control, purchase management, sales management, production planning, human resource management, customer relationship management and the like, ensures the accuracy and consistency of data, and realizes the cloud management of the enterprise through a data sharing function. All the modules can obtain needed data and information in real time, and seamless transmission and cooperative work of the information are achieved.

According to the distributed identity management system and method based on the block chain, the identity information of the user is stored on the distributed nodes by using the characteristics of the block chain, and the security of the information is protected by using an encryption algorithm. Each user has a unique identity label, and the identity label is written into a block of the block chain and is managed and verified through an intelligent contract. The user can control the access and management of the identity information of the user through the private key without depending on a centralized identity authentication mechanism. In addition, the VC template providing the VC service is subjected to uplink processing, and the consistency and compliance of the VC certificate are ensured from the source. According to the invention, the problem of verification information forgery of the distributed identity management system can be solved, and the security and credibility of identity verification are improved.

This invention relates to the field of bid document management technology, and in particular to an automatic bid document review method and system based on natural language processing. The method includes: identifying target sections; determining historical performance and financial information; judging whether false performance exists; analyzing the complete sentences containing target keywords; calculating material scores; determining price deviation; and determining the review result. This invention achieves multi-dimensional and comprehensive review of bid documents by intelligently analyzing multiple sections such as qualifications, risks, materials, and pricing. This effectively improves the comprehensiveness and depth of the review. Utilizing natural language processing technology, it can accurately identify and extract key information from bid documents, overcoming the subjectivity and limitations of traditional manual review. Quantitative assessment based on risk level significantly improves the accuracy and relevance of risk identification. By comprehensively weighing material scores and price deviation, it significantly improves review efficiency.

The invention provides an engineering information data management method based on a block chain, and relates to the technical field of block chains, the method is applied to a first server, and the method comprises the following steps: obtaining to-be-processed engineering information data; the synchronous broadcast is sent to the plurality of node servers, reply information sent by a second server in the plurality of node servers is received, and the reply information comprises a second public key of the second server and equipment information; respectively sending the equipment information of each second server to other second servers for verification; after the information that the plurality of second servers pass the verification of the equipment information is obtained, encrypting each piece of engineering information data by adopting a second public key to obtain encrypted data, so that the encrypted data can be decrypted by adopting a second private key corresponding to each second public key; and sending the encrypted data to the second server according to the communication address of each second server. According to the invention, the security of engineering information data management can be improved.

This invention discloses an intelligent visual prosthesis system and encoding method. The system includes an external sensing processing unit and an internal implanted stimulation unit. The external sensing processing unit includes at least an environment sensing unit and a first data processing unit, and the internal implanted stimulation unit includes at least a stimulation signal generation unit and an electrode array. The environment sensing unit is used to acquire a target image. The first data processing unit is used to match the current scene to a preset lighting scene mode according to the image features or ambient illuminance of the target image, independently configure anchor points for the corresponding image grayscale value boundaries for the matched lighting scene mode, and generate a grayscale-charge density mapping relationship corresponding to the lighting scene mode. Then, the grayscale value of each pixel of the target image is mapped to the corresponding target charge density, and a stimulation command is generated and output to the stimulation signal generation unit. The stimulation signal generation unit is used to generate an electrical stimulation pulse sequence according to the stimulation command and a preset reference pulse width and output it to the electrode array.

The application belongs to the field of wisdom city space-time information platform, and is a space-time service unified management and intelligent monitoring method based on APISIX gateway. Through Admin API, upstream mapping tables of city and district levels are established to realize decoupling of back-end address and external access address, support hot update and non-restart traffic switching during service adding, deleting, modifying and inquiring, construct a finite state machine for service approval state, automatically trigger creation, update or deletion of gateway routing configuration through an event-driven mechanism, develop a quota plug-in embedded in the access stage of APISIX, use Nginx shared memory to configure a composite key with service ID: application ID: plug-in context, call the incr method to atomically increment the record request number, calculate the remaining quota, automatically reset when TTL expires, and return HTTP 429 when exceeding the limit, configure the http-logger plug-in to send structured logs to a log server, calculate service dimension and application dimension indicators in real time through access records and expose APIs, and configure three types of composite early warning rules for service availability, service performance and access compliance.

The invention relates to the field of marketing risk prevention and control, in particular to a marketing business risk prevention and control method for spot transaction scenes. The technical problem is that when risk prevention and control are carried out on marketing business in a spot transaction scene, market research and analysis are carried out on a market by collecting transaction data on the market so as to understand a market trend and a strategy of a competitor as a main index for risk prevention and control, and only the current condition of the market is considered. The market is difficult to comprehensively analyze and research; according to the technical scheme, the marketing business risk prevention and control method for the spot transaction scene comprises the steps of data processing and identification, external risk analysis and internal process risk analysis; by setting the preset specific data interface, the prediction data of the market development can be input, so that the market development can be effectively predicted, the market development can be combined with the current condition of the market, the market demand can be effectively analyzed and predicted, and effective data support is provided for risk prevention and control.

The application relates to the technical field of emergency management, and discloses an emergency response and early warning system for a sudden combustion and explosion event, which comprises a multi-source data access module, which is used for collecting target equipment data and environment benchmark equipment data of energy storage equipment or a centralized charging site in real time, including temperature, current, voltage, fan state and smoke / odor sensor data, and pre-processing the collected target equipment data and environment benchmark equipment data; an abnormal index preset module, which is used for presetting a composite abnormal index representing early signs of thermal runaway and risk grading standards; and a same-site benchmarking module, which is based on the collected target equipment data and environment benchmark equipment data. The same-site benchmarking module is adopted, the environment benchmark data and abnormal acceleration change trend calculation are carried out, the technical effect of identifying the composite abnormal index in an extremely early stage is achieved, early warning is realized, and the problem that the safety window period for the operation party to take initial disposal actions is short is solved.

This invention discloses an intelligent CTD sampling control method and system combining tidal current prediction, relating to the field of marine observation technology. The method includes: generating tidal current predictions by fusing historical tidal elements and numerical model outputs, and planning candidate sampling windows; real-time acquisition of multi-source observation data to form standardized observation vectors, calculating the deviation from the predicted values ​​and fusing the vertical shear force intensity factor to perform rolling corrections on the predictions and update the sampling windows; comparing real-time observation data with safety thresholds to generate operational access instructions, issuing control instructions under permissible conditions, and dynamically adjusting sampling parameters and triggering resampling based on profile data quality coefficients; synchronously monitoring abnormal events, triggering emergency recovery, and deferring the task to subsequent candidate windows. By constructing intelligent closed-loop control, introducing vertical shear force early warning, and a parallel processing architecture, adaptive, highly safe, and highly reliable CTD sampling operations under complex sea conditions are achieved.

The invention discloses a robot navigation method fusing U-net semantic segmentation, and relates to the technical field of computer vision and robots. Comprising the steps of S1, collecting an original image of a front road scene in real time; s2, performing semantic segmentation processing on the original image to generate a semantic segmentation prediction map and a probability distribution map; and S3, based on the probability distribution diagram, analyzing the spatial distribution and boundary trend of the passable area, and calculating a structured control parameter at the next moment. Accurate recognition of passable areas, static boundaries and dynamic obstacles in a complex road environment is realized, an upper and lower double-layer hardware architecture design is adopted, a semantic perception task with a high computing power requirement is separated from a motion control task with a high real-time requirement, the upper industrial personal computer is responsible for image processing and decision making, and the real-time performance of the robot is improved. The lower STM32 single-chip microcomputer is responsible for PWM signal output and motor driving, and then fast response and stability of bottom layer control are ensured under the condition that efficient operation of the deep learning model is ensured.