9results about How to "Improve analyzability" patented technology

The invention discloses an artificial intelligence-driven burn wound assessment method and system, and relates to the technical field of medical information processing and intelligent diagnosis, and the method comprises the following steps: S001, employing a fixed imaging attitude to collect continuous short-sequence wound image frames, calculating a brightness change curve of adjacent image frames, generating a light and shade rhythm track, and drawing a beat frequency prompt band, the method is used for marking a light source flicker rule and establishing an initial reference baseline of brightness change. Through brightness breakpoint identification, error shooting parameter calculation, light source phase jitter and inverse rhythm optical shutter regulation and control, active separation and reverse coupling of illumination rhythm and sampling rhythm are realized, periodic flicker interference is effectively eliminated, the brightness stability and texture reduction degree of a wound image are improved, an artificial intelligence evaluation result is more accurate and reliable, and the artificial intelligence evaluation efficiency is improved. And the objectivity and safety of clinical diagnosis are improved.

The embodiment of the invention provides a dwell pressure adjusting method, which is applied to an upper computer and a servo driver, and comprises the following steps that: the upper computer configures mapping parameters of a pressure value and an analog quantity value and issues the mapping parameters to the servo driver, and the servo driver calculates a dwell pressure value based on a linear calibration model; a servo motor is controlled to execute self-learning to determine a contact point origin machine of the pressing process; the upper computer issues a force control instruction to the servo driver through the EtherCAT bus; the servo driver converts an analog quantity signal fed back by the pressure sensor based on a linear calibration model to obtain a real-time pressure value, adjusts the torque of the servo motor by taking the original point of the contact point as a reference, and feeds back a state to the upper computer through an EtherCAT bus; an upper computer reads a process data packet through a Modbus bus and analyzes the process data packet to obtain a pressure-time relation oscillogram, complete and synchronous acquisition and tracing of process data are achieved through double-bus cooperation based on built-in high-precision calibration and closed-loop force control of a driver, and the precision, stability and analyzability of a pressure maintaining process are improved.

The application discloses an abnormality detection method for long-time and large-capacity recording of a digital oscilloscope, and the method comprises the following steps: acquiring a parallel sampling data stream through high-speed ADC sampling of a front end of the digital oscilloscope; performing trigger alignment processing on the parallel sampling data stream through FPGA; performing multi-dimensional feature extraction on waveform data segments after the trigger alignment; obtaining a fusion feature value through normalization and weighted fusion of the features; and further performing classification and statistics on the fusion feature value through an online incremental clustering mode, identifying abnormal waveforms according to probabilities of various features, and outputting an abnormal category and statistical information, so that stable and sustainable operation of the abnormality detection in a long-time and large-capacity recording scene is realized.

The invention relates to a JavaScript code anti-obfuscation method based on an AST abstract syntax tree, and belongs to the technical field of software security, program analysis and code reverse engineering. Compared with the prior art, the method has the advantages that simple text matching is exceeded, and the'intention 'of codes can be understood through semantic analysis of AST, so that complex confusion transformation is accurately restored.

This application relates to a method for predicting the evolution of online public opinion under the intervention of AI agents and online trolls. The method includes: acquiring social media user data; constructing a weighted directed social network containing ordinary netizens, online trolls, and commentary-type AI agents and identifying node types; mapping text content to opinion values, setting the opinion values ​​of online trolls to fixed values, and setting the commentary-type AI agents to generate targeted comment opinion values ​​for different target users; calculating the individual confidence threshold of ordinary netizen nodes, and performing opinion updates based on the extended Deffuant-Weisbuch dynamics equation; iteratively updating until convergence, and outputting the final opinion distribution as the prediction result. This invention, by introducing multi-agent heterogeneous interaction and human intervention, solves the problem of existing models' inadequate characterization of complex public opinion environments, significantly improving the accuracy and modeling completeness of online public opinion evolution prediction.

This invention discloses a method and system for detecting and evaluating the settlement of buried pipelines based on ground-penetrating radar (GPR). The detection method acquires B-Scan mask images of shallow-buried pipelines, extracts the overall and local characteristics of target hyperbolic reflection signal feature points in the images, removes singular points, performs curve fitting on all valid target hyperbolic reflection signal feature points, and calculates and scores the depth and wave velocity values ​​corresponding to the target feature points to obtain the pipeline burial depth. The evaluation method, based on the pipeline settlement detection results, identifies the location of maximum settlement deformation by using the angle formed by the height change between two points on the pipeline, and predicts the location where the risk of fracture in the detected section may occur. The detection system implements this detection method, and the evaluation system implements this evaluation method. This application solves the problem in engineering measurements where hyperbolic reflection signals with characteristic damage caused by electromagnetic wave attenuation and coupling cannot be effectively calculated, significantly improving the data's processability and analyzability.

The embodiment of the invention provides a space-time research and judgment method, a research and judgment system, electronic equipment and a storage medium. The method comprises the following steps: acquiring network access data corresponding to an entity to be researched and judged, and processing according to a preset feature extraction rule to obtain basic feature information and associated feature information; constructing a spatial-temporal feature sequence according to the basic feature information and the associated feature information, and inputting the spatial-temporal feature sequence into a trained feature recognition model to obtain behavior feature information; comparing the behavior characteristic information with behavior characteristic conditions in a behavior rule base to obtain a characteristic comparison result; according to a feature comparison result, when it is determined that the entity to be researched and judged meets a preset research and judgment condition, determining an expanded network entity according to the associated feature information; and according to the research and judgment result of the entity to be researched and judged and the expanded network entity, generating and outputting a space-time research and judgment result. According to the invention, the time-space research and judgment of the target entity and the associated network space thereof are realized, and the comprehensiveness and accuracy of identification are improved.

The application relates to the field of image recognition and discloses an obstacle cross-frame tracking method, device and equipment and a storage medium, which comprises the following steps: acquiring an obstacle recognition result in a first detection image, and generating a tracking query based on the obstacle recognition result; extracting an image feature of an obstacle in a second detection image, and obtaining a new obstacle query based on the image feature; inputting the tracking query and the new obstacle query into a preset obstacle tracking model, tracking and identifying the obstacle in the second detection image through the obstacle tracking model, and obtaining a tracking and identifying result. Through the method, the query value of the obstacle feature between two continuous frame images can be compared based on image information, the tracking process for consecutive images in time sequence is directly completed implicitly in the obstacle tracking model, the complexity of the algorithm architecture is reduced, and the optimizability and analyzability of the whole tracking process are improved.

This application relates to a domain-specific language compiler for cache coherence protocols, belonging to the field of computer architecture modeling and simulation technology. The compiler takes a high-level abstract specification of the cache coherence protocol as input and automatically converts it into cache controller and / or directory controller code executable by a periodic precision simulator. Through systematic mapping and translation of the protocol's finite state machine, event-triggered mechanism, concurrent transaction management, and asynchronous hardware interaction, it achieves event-driven, non-blocking control logic generation. Simultaneously, the compiler supports network communication code generation, debug tracing injection, and formal logical equivalence checks. Furthermore, it incorporates a performance constraint-aware optimization module to automatically optimize the generated state machine, thereby improving simulation efficiency, reducing development complexity, and enhancing verifiability while ensuring the semantic correctness of the protocol.