8 results about "Reference analysis" patented technology

This method enables the fully automated creation of a wiki from a text corpus. The lists of articles to be created are generated using either a vector-based or a purely frequency-based analysis. The actual text creation step always employs a RAG (Reference Analysis Group) method, in which the LLM (Licensed Life Sciences) uses a vector database to create well-founded, context-appropriate articles. This results in a scalable, well-structured, and linked knowledge system that can be used in various disciplines—from corporate and legal or medical documentation to large scientific archives.

The application discloses a method for de-obfuscation and feature extraction of phishing documents and application thereof in attack detection, wherein the de-obfuscation comprises obtaining obfuscated macro code of the phishing document, constructing a hint engineering template by using a pre-trained language model, analyzing an obfuscated logic structure and generating de-obfuscation rules and restoration strategies; the obfuscated macro code is structured into an abstract syntax tree by using an analysis tool, typical obfuscated patterns are matched based on a regular expression, function execution simulation and cell reference analysis are combined, preliminary restoration of the structure, restoration of control flow semantics and operation path construction are realized; according to the de-obfuscation rules and the abstract syntax tree, the obfuscated structure is converted into readable macro statements, a macro code instruction sequence without obfuscated semantics is generated, and a semantic sequence after de-obfuscation is output. The feature extraction comprises extraction of word features, Token features, abstract syntax tree features and relationship features. The application breaks through the bottleneck of traditional phishing attack detection and difficulty in identification of obfuscated documents, and improves the detection accuracy of phishing document attacks.

The application relates to a memory object reference analysis method and device, computer equipment, a storage medium and a computer program product. After a memory object query request is acquired, memory object address information is searched. According to the memory object address information, a socket connection mode is used to access a memory monitoring object. Memory object serialization information fed back by the memory monitoring object is acquired. The memory object serialization information is deserialized to acquire memory object reference information corresponding to the memory object query request. Memory object reference analysis information is generated according to the memory object reference information. The memory object reference analysis method can acquire memory object serialization information from the memory monitoring object through the socket connection, thereby obtaining corresponding memory object reference relationships through deserialization, realizing memory object reference relationship identification and display in a running process of the memory monitoring object, and performing more in-depth memory object reference analysis.

This invention discloses an intelligent electro-pulse therapy control method based on AI adaptive feedback, relating to the field of electro-pulse therapy control. The method includes the following steps: collecting biofeedback signals from the therapy user and simultaneously collecting the user's subjective feedback data; converting the subjective feedback data into effective subjective data and performing preliminary analysis of the feedback analysis data between different biofeedback signals and subjective feedback data; deeply analyzing the influence of different biofeedback signals on the subjective feedback data, and simultaneously constructing historical reference analysis schemes and predictive reference analysis schemes to calibrate the impact on the feedback analysis data, obtaining feedback reference data; and intelligently controlling the intelligent electro-pulse therapy based on the feedback reference data. This invention addresses the problem that existing electro-pulse therapy control technologies lack intelligent and accurate acquisition of pain perception, resulting in an inability to adjust the intensity of the electro-pulse in a timely and accurate manner.

The present application relates to the field of weather radar, and more particularly to a zenith rotating dual-polarization radar calibration and diagnosis method, system, device and medium, wherein the method comprises: if a preset trigger condition is met, controlling the radar antenna to perform vertical pointing to the zenith; driving the radar antenna to perform azimuth rotation scanning, collecting polarization base data with azimuth full-circle distribution characteristics and radial height level characteristics; filtering out interference echoes and non-liquid precipitation echoes by screening and cleaning the polarization base data, obtaining a reference analysis sample; performing multi-dimensional modeling on the reference analysis sample to separate out fluctuation errors, obtaining calibration characteristic quantities and using them for online data compensation, and according to the comparison result of the standard deviation profile of the reference analysis sample and the theoretical accuracy index, mapping and identifying the hardware component state of the radar to output diagnosis information. Thus, while improving the calibration accuracy of the dual-polarization radar, the present application significantly enhances the accurate diagnosis capability of the deterioration risk of the radar bottom components.

In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving input data from at least one external data aggregator; utilizing a trained machine learning algorithm to generate a database of known queries; receiving subsequent input data from the at least one external aggregator; automatically updating the database of known queries associated with the plurality of users; utilizing the trained machine learning algorithm to perform a cross-reference analysis to determine a presence of a data record within the database of known queries; dynamically removing the data record from the database of known queries; utilizing the trained machine learning algorithm to predict a trigger associated with the presence of the at least one data record; and instructing a computing device to initiate a verification of the presence of the at least one data record.

A computer system obtains digital image data of a live subject; extracts one or more reference attributes of the subject based on the image data; executes a machine learning (ML) model using the reference attribute(s) of the subject as input to generate avatar customization data as output; and modifies a graphical avatar based on the avatar customization data generated by the ML model. A computer system extracts, by a reference analysis engine, one or more reference attributes of a reference image or graphical avatar; extracts, by a user image analysis engine, one or more target attributes of a target user image; executes an ML model using the reference attribute(s) and the target attribute(s) as input to generate target image modification data as output; and generates, by a virtual try-on engine, a modified version of the target user image based on the target image modification data generated by the ML model.

According to the invention, a brake element (1) is provided, comprising a base body (2) and a friction layer (3), wherein the friction layer (3) comprises a steel which has the following reference analysis:10⁢-15⁢%⁢ by⁢ weight⁢ Mn 18-24⁢%⁢ by⁢ weight⁢ Cr⁢ <1⁢%⁢ by⁢ weight⁢ Si <1⁢%⁢ by⁢ weight⁢ N<0.1%⁢ by⁢ weight⁢ CResidual⁢ Fe .