9results about How to "Avoid verification process" patented technology

The embodiment of the invention provides a verification method, computing equipment and a verification system. The verification method comprises the following steps: acquiring operation information of a to-be-verified processing unit; carrying out convergence anomaly analysis on the operation information, and determining a convergence anomaly operator in the to-be-verified processing unit; based on the operator type of the convergence anomaly operator, a target verification tool corresponding to the operator type is called to verify the convergence anomaly operator, a verification result is obtained, the target verification tool is constructed based on a convergence constraint corresponding to the operator type, and the convergence constraint is used for constraining the complexity of verifying the convergence anomaly operator. The verification quality is effectively improved, and the convergence speed of the verification process can be accelerated by optimizing the verification complexity of the convergence anomaly operator, so that the verification period is shortened, and the verification efficiency is improved. In addition, the innovation scheme provided by the embodiment of the invention can be used for the RISC-V processor.

The present invention discloses a method, device and storage medium for determining a home source address, including: determining an IPv6 address that initiates a malicious attack; converting the IPv6 address to obtain a converted address value; determining the home source address of the IPv6 address according to the converted address value in an address home library, wherein the address home library contains a correspondence between the address value and the home source address. The present invention can be used to implement IPv6 home source address verification to prevent malicious attacks. The method is flexible and diverse, which is conducive to verification and application. The scope of promotion and application can be large or small. The implementation is simple and has a good application scenario, and large-scale promotion and expanded application can be carried out after the product is realized.

The invention discloses an RPA task execution retry optimization method based on machine learning, and relates to the technical field of machine learning, an external tool is not needed, a developer can directly complete debugging in a browser, front-end and back-end real-time communication is achieved through the WebSocket technology, the developer can monitor the execution state of each process link in real time, and the execution efficiency is improved. Therefore, fine-grained control is carried out on the process anytime and anywhere; besides, global variables and the capability of skipping to any link are modified in real time, so that a developer can quickly verify different logic branches under the condition of not restarting a process; most importantly, the system and a low-code designer are seamlessly integrated, and design, debugging and operation are simultaneously carried out in a unified interface, so that the switching cost in the development process is reduced, the whole development, test and debugging process is smoother, and the development efficiency and experience are remarkably improved.

The embodiment of the present application provides a test method, apparatus, device and storage medium, the method comprising: obtaining a test record set, the test record set including at least one test record; determining a first test record to be executed in the test record set; determining a target test system from at least two test systems according to the first test record; sending test information to the target test system, the test information including the test time. It is used to shorten the test time of the test system, improve the test efficiency of the test system, and thus improve the test efficiency of the financial data processing system including the two test systems and the operation quality after going online.

The utility model discloses a mining intrinsic safety type access controller, relates to the technical field of mine access control, and comprises a control shell and an electric control mechanism, the left side and the right side of the control shell are provided with fastening holes, one side of the control shell is connected with a sealing cover plate in an attached mode, the outer side of the sealing cover plate is connected with tempered glass in a penetrating mode, and the outer side of the sealing cover plate is connected with the electric control mechanism in a penetrating mode. A positioning mechanism is arranged in the control shell, the positioning mechanism is used for clamping the electric control mechanism and the acquisition camera, the equipment is prevented from shaking in the use process, a heat dissipation mechanism is arranged below the positioning mechanism, and the heat dissipation mechanism is used for carrying out circulating heat dissipation on the electric control mechanism and other equipment. The automatic electric control mechanism can be installed in the control shell and can move freely along with the interior of the control shell, meanwhile, the electric control mechanism and the camera are clamped according to use requirements, and the situation that in the use process of the camera, due to the fact that the angle and height are too low or too high, the camera cannot accurately collect and verify the face is avoided.

The application relates to a kind of implementation methods of verifiable Internet of Things device data asset transaction, based on the data seller, blockchain and data buyer involved in Internet of Things data asset transaction system, the process for realizing verifiable data asset transaction is as follows: data seller publishes encrypted data on blockchain through smart contract, data buyer requests data according to needs and submits verification request.Smart contract is responsible for verifying the integrity and authenticity of data, and transmits decryption key to data buyer after verification.The data buyer decrypts the data using the key and completes the transaction.If the buyer finds that the decrypted data is abnormal, the smart contract is called to initiate arbitration.Through the confusion encryption mode, RSA accumulator technology, hash verification mechanism and on-chain arbitration mechanism, these attack behaviors are effectively resisted, and the privacy, integrity and verifiability of data transaction are ensured.

A method for counting personnel entering and exiting a coal mine based on combined target tracking includes the following steps: the counting system is started and enters the working state; a bounding box of the mine entrance area in the video surveillance is selected; the corresponding video stream is captured from the obtained surveillance video; the output personnel detection location box and safety helmet detection location box are input into the personnel tracking module, and the target tracking sequence of personnel and the target tracking sequence of safety helmets are output; the position status of the safety helmet is used to assist the matching score of personnel tracking; the IOA between the personnel location detection box and the mine entrance area in each frame of the target tracking sequence of each personnel is calculated; the IOA between the safety helmet location detection box and the mine entrance area in each frame of the target tracking sequence of each safety helmet is calculated; the calculation results are used to define whether each personnel and safety helmet have entered the mine; and the number of people entering and exiting the mine is counted based on the matching results.

The invention relates to the field of model optimization, and discloses a method, device, electronic device, and storage medium for optimizing the consistency of a photoresist model. The method comprises step S11: after performing current generation search and simulation on simulation item parameters in the photoresist model, shifting a test pattern corresponding to the photoresist model; step S12: determining a photoresist parameter density difference corresponding to a key size at a preset sampling point after the test pattern is shifted; step S13: determining a function value of a cost function according to a relationship between the photoresist parameter density difference and a preset density difference threshold; step S14: performing next generation search and simulation on the simulation item parameters in the photoresist model, and entering step S11 until the number of generations searched and simulated for the simulation item parameters in the photoresist model is equal to the preset algebraic threshold; and step S15: determining a minimum value among all function values, and taking the minimum function value as a final result of photoresist optimization, so as to improve the consistency of the photoresist model.