8results about How to "Ensure availability" patented technology

This disclosure proposes a method for synthesizing multimodal data for decision-making attribution explanation in the mining industry, comprising the following steps: First, extracting causal logic from industry texts to construct a structured rule base; second, collecting on-site multimodal data and filtering out data pairs strongly correlated with rules through scenario-based weight modeling and cross-modal association mechanisms; third, using a multimodal generative adversarial network with rule constraint mechanisms and combined with rule mutation technology to synthesize multimodal data with complete logical chains and covering various complex working conditions; finally, ensuring data quality and achieving self-evolution of the knowledge base through a three-level verification and rule feedback mechanism, and storing qualified data in a hybrid storage database. This invention solves the problems of complex causal relationships and scarce high-quality training samples in the mining field, and can automatically and in batches generate logically rigorous and scenario-diverse multimodal data, improving the training efficiency and generalization ability of attribution decision models.

The application discloses a high-resolution satellite image urban area shadow-removed ARD production method and device, and belongs to the technical field of remote sensing image processing. The method comprises the following steps: firstly, screening out images covering urban areas; performing radiation calibration on high-resolution satellite images covering urban areas to obtain apparent radiance images; based on the apparent radiance images, performing preliminary shadow detection by using a pre-trained deep learning model; using a near-infrared band of an atmospheric-corrected ground reflectivity image, performing false detection elimination on the preliminary detection result by adaptive threshold segmentation to obtain a final shadow mask; performing histogram matching processing on the shadow area based on the shadow mask on the atmospheric-corrected ground reflectivity image to realize shadow removal; and finally, outputting the shadow-removed ARD product. The application significantly improves the shadow detection precision and the quantitative reliability of the ARD product, and is suitable for large-scale ARD production of high-resolution satellite images in urban areas.

The application relates to the technical field of knowledge base generation, and particularly discloses an education knowledge base content generation method and system based on AI big data. The method comprises the following steps: comparing user answer content with answer information to obtain a matching degree, calibrating positive samples and negative samples to train an evaluation model, and determining a reference standard score according to the quantity relationship between the positive samples and the negative samples; based on the reference standard score and a tolerance threshold, a plurality of candidate knowledge contents are screened to calibrate them as stable knowledge contents or to-be-corrected knowledge contents, and are output. By constructing an evaluation system based on user real answer data and an evaluation standard reflecting the actual application effect of the knowledge content, and automatically calibrating the evaluation standard according to the data distribution, objective screening and continuous iteration of the knowledge content are realized, and the accuracy and reliability of the knowledge base content are improved.

This invention discloses a text correction method, apparatus, electronic device, and storage medium. The method includes: acquiring first text, which is a text result generated by speech recognition of target audio data; detecting the first text using a target text detection model to obtain a first detection result; wherein the target text detection model is a pre-trained neural network model used to detect whether the text input to the model is a reference type statement; in response to the first text not being a reference type statement, performing text correction on the first text using a target text correction model to obtain a text correction result; the target text correction model is a pre-trained neural network model used to perform character recombination on the text input to the model and filter reference noise characters for text correction. This invention enables automatic detection and correction of text results from speech recognition in multi-speaker mixed scenarios.

This invention relates to the field of automatic control of nitrogen valves, and particularly to an automatic control method for nitrogen valves based on intelligent sensing. First, based on the measured values ​​of the acquired original sensing variables, preprocessing is performed to obtain preprocessed measured values ​​of the sensing variables. Based on the preprocessed measured values ​​of the sensing variables, a time-varying energy consistency fusion algorithm is used to obtain the state-driven energy value of the sensing variables. Based on the state-driven energy value of the sensing variables, the contribution of the sensing variables is determined, and a fusion situation indicator is constructed. Then, based on the fusion situation indicator, a control potential energy function is constructed using a continuous potential energy-driven valve position decision algorithm. Based on the control potential energy function, the valve adjustment speed is obtained. This method solves technical problems such as insufficient utilization of multi-source sensing information, inaccurate state assessment, delayed adjustment response, and lack of effective intervention for abnormal risks.

The application discloses a Bluetooth transmission method and system, the method comprises the following steps: sending a plurality of Bluetooth data packets while detecting Bluetooth connection; after sending the Bluetooth data packet each time, judging whether the ACK response is correctly received; if yes, increasing the initial maximum transmission window of Bluetooth in response to the correct reception of the ACK response; if not, using dichotomy to find the optimal window size of the current transmission between the initial maximum transmission window and the transmission window threshold, the transmission window threshold being smaller than the initial maximum transmission window; repeatedly calculating the optimal window size of several transmissions, and determining the best Bluetooth transmission window based on the optimal window size of several transmissions for data transmission; the application can improve the efficiency of Bluetooth transmission data.

This invention discloses a method, apparatus, medium, and device for generating prompt words based on a large language model. Belonging to the field of prompt word generation, this application acquires multi-source runtime data from a development scenario processed according to a model context protocol, performs semantic understanding on this data using a large language model, and selects the optimal prompt word template suitable for the current development intent from a pre-set prompt word template library based on template metadata specifications. Further, according to the semantic mapping relationship established by the model context protocol, parameter values ​​matching the optimal template are selected from the multi-source runtime data, and the accuracy and consistency of the parameter values ​​are ensured through multiple verifications. Finally, the verified target parameter values ​​are filled into the optimal prompt word template to generate a complete prompt word for large model inference. This application effectively solves the problem that existing technologies cannot accurately and efficiently generate prompt words for large language models.

This invention discloses a method and system for recovering encrypted files based on key context. The method includes: acquiring the underlying binary image of the target storage medium; parsing the file system structure to locate the inode table; filtering encrypted file inodes whose status is deleted, and extracting key information including data block pointers, master key identifiers, and encryption policy descriptors; obtaining the master key from the associated system kernel based on the master key identifier, and calculating and generating a file content encryption key in combination with the encryption policy descriptor; decrypting the extracted encrypted data blocks using the key, and reassembling them in sequence to complete file recovery. This invention avoids the huge computational consumption of traditional brute-force attacks by directly utilizing residual metadata of the file system and the master key cached by the kernel for key reconstruction, and, based on the general FBE mechanism, does not rely on specific vulnerabilities, significantly improving the recovery efficiency and applicability for Android FBE encrypted files.