2results about How to "Strong randomness" patented technology

The application belongs to the technical field of information processing, and particularly relates to a document-level relation extraction method based on a generative model, which comprises the following steps: firstly, in the training stage, a generative model is used to compress and refine the document, and the relation summary of the subject and object in the document is extracted, so that information closely related to the target is screened out; secondly, in the testing stage, a lightweight discriminant module is introduced, and the relation summary output by the generative model is mapped to a predefined relation category; and the generative model has self-adaptive learning ability and can dynamically and autonomously learn human carefully selected examples to generate output closer to human intention.

This invention relates to the field of chaotic system theory and discloses a quantum image encryption algorithm based on chaotic systems and DNA dynamic coding. The algorithm includes a quantum image coding module, a chaotic sequence generation module, a DNA dynamic coding and operation module, and a central control module. The algorithm also integrates a key management unit. By using an enhanced quantum phase representation method to convert classical images into quantum images, and utilizing quantum gate operations controlled by chaotic sequences to achieve quantum scrambling of pixel positions and preliminary diffusion of pixel values, the system can efficiently perform preliminary confusion and perturbation of image information directly at the quantum level, laying a secure preprocessing foundation for subsequent encryption. By using a parallel multi-chaotic system to generate a dynamic key stream and introducing a dynamic perturbation mechanism based on image hash values, the generated key stream has stronger randomness and is dynamically related to the plaintext image content, enhancing its ability to resist security threats.