6 results about "Cognitive technology" patented technology

The invention discloses an ultra-high performance concrete knowledge graph construction and mechanism interpretation method based on graph retrieval enhancement generation, and belongs to the technical field of ultra-high performance concrete knowledge graph construction and mechanism cognition. The method comprises the following steps: acquiring a plurality of literatures associated with ultra-high performance concrete; based on a plurality of literatures associated with the ultra-high performance concrete, constructing an ultra-high performance concrete knowledge graph; based on the ultra-high performance concrete knowledge graph, executing self-adaptive length path retrieval on the target origin-destination node to obtain at least one first candidate evidence chain corresponding to the target origin-destination node; and inputting the target instruction and each first candidate evidence chain into the generative model to obtain a corresponding mechanism interpretation text. According to the method, the mechanism explanation of the knowledge of the ultrahigh-performance concrete with high credibility can be efficiently obtained.

The invention relates to the technical field of individualized cognition, in particular to an individualized cognitive decline risk prediction method and system based on multi-mode data fusion. According to the method, multi-modal longitudinal evidence-based data is integrated on the basis of a group-level pathology law, a multi-scale causal link map capable of reflecting the complete period of cognitive decline is formed, pathology time axis alignment and individualized feature normalization are achieved, the dynamic pathology process of individual specificity can be captured, and the accuracy of the pathology process is improved. By fitting individual exclusive multi-scale causal parameters and constructing a time sequence cascade digital twinborn body, forward causal simulation can be executed on multiple time scales, a cognitive decline core driving path is directly revealed, and individual risk quantification and intervention targets are generated. Detection of early hidden pathological signals, dynamic modeling of individual heterogeneity and comprehensive analysis of a multi-channel pathological mechanism are achieved, the ultra-early prediction precision of cognitive decline and individualized intervention suitability are remarkably improved, and a full-period prediction system capable of being iteratively optimized continuously is formed.

The application discloses a kind of phobia treatment systems based on immersive VR and gaze adaptive virtual cognitions, at least including scene configuration module, task control module, eye movement data acquisition device, data processing module and psychological intervention module, it is applied to the treatment and training in the aspects such as psychological disorder, social skill based on the virtual cognitions (Virtual Cognitions, VCs) technology of gaze point adaptation, especially for the exposure treatment of phobia patient, the system can be applied in large scale, it is favorable to with more efficient, convenient way, improve the treatment effect of phobia and other psychological disorder diseases, help patient to walk out the gloom of fear.

The present application belongs to the technical field of machine high-order cognition, and particularly relates to a method for enhancing the humor reply capability of a pre-training language model of machine high-order cognition.The method comprises the following steps: establishing a connection between a regular text and a humorous text, including constructing an interpretable data set composed of a plurality of preceding text-humor reply pairs, each preceding text-humor reply pair having a humor chain and a humor mind map, and showing the knowledge and logical reasoning process required for generating a humor reply; evaluating and improving the humor reply capability of the pre-training language model, including designing a humor sentiment style classification task and a humor rewriting task as auxiliary humor replies in a multi-task training manner; and designing an encoder-decoder framework, injecting the humor chain and the humor mind map into the pre-training language model, and enhancing the humor reply capability of the pre-training language model based on a multi-task learning manner and using the two auxiliary tasks.The present application can greatly enhance the humor reply capability of the pre-training language model.

The application belongs to the technical field of situation awareness, and specifically discloses an interpretable target group behavior discrimination method, which comprises the following steps: acquiring multi-source situation information data of a detected target group; obtaining a space-time distribution feature vector of the detected target based on the multi-source situation information data; constructing a to-be-learned double-layer graph structure based on the multi-source situation information data and the space-time distribution feature vector; discriminating the behavior category of the detected target group through a relational graph neural network based on the space-time distribution feature vector and the to-be-learned graph structure; and making the discrimination result of the relational graph neural network interpretable through a deep structure causal model SCM.

The application relates to the field of intelligent cognitive technology and discloses an improved intelligent cognitive robot cognitive module based on ACT-R, which comprises cognitive modeling intelligent unit modules, feature processing intelligent unit modules, understanding calculation intelligent unit modules, reasoning prediction intelligent unit modules and association recommendation intelligent unit modules which are connected in sequence. The application solves the problems that the existing cognitive calculation does not involve human emotions and implicit knowledge and cannot more truly simulate the human cognitive decision-making process.