2259 results about "Data file" patented technology

A method is provided for dynamically generating a digital watermark for a data file. The method includes receiving a request to access the data file from a user; dynamically generating an encryption key based on at least one parameter selected from the group consisting of the identity of the user, the time of access, and the mode of access; embedding a digital watermark into the data file using the dynamically generated encryption key, wherein the digital watermark is unique to the request; providing access to the data file with the embedded digital watermark to the user; and storing information related to the encryption key and the parameters used for its generation in a secure database.

The invention relates to the field of text processing, in particular to a bidding document information extraction method. Comprising the following steps: segmenting a bidding and tendering file into pages, and identifying the pages to obtain corresponding texts; generating complementary text description for images and tables in the page and adding the complementary text description to the tail of a text corresponding to the page to form an enhanced text block sequence; matching a label from the text block sequence according to a pre-constructed hierarchical label system, and generating a corresponding cue word template according to the label and a pre-constructed cue word template library; inputting the cue word template, the enhanced text block sequence and the context text abstract as a combination into a large language model to obtain a structured extraction result with a hierarchical relationship; and matching the extracted entity content with a local dictionary, carrying out aggregation arrangement on a result after the matching is passed, and outputting a structured data file. On the premise that the model does not need to be retrained, the illusion risk of the generated content is reduced.

The invention relates to the technical field of three-dimensional models, in particular to a drawing method for making a three-dimensional model based on three-dimensional laser point clouds, which comprises the following steps of: sequentially reading point cloud data files of the three-dimensional laser point clouds, inserting coordinate values of each point into an octree structure, and when octree node buffer areas in a memory are full, drawing a three-dimensional laser point cloud into the octree structure; and writing the node data in the buffer area into a hard disk, and traversing the hard disk octree node set from bottom to top. According to the method, the three-dimensional laser point cloud data is inserted step by step, and the hierarchical aggregated octree structure is utilized, so that the point cloud data processing efficiency is effectively improved, and the memory occupation pressure is reduced; representative points in an octree structure are fused with an average normal to construct a continuous function field, a grid model is adaptively generated in a multi-detail-level mode, and the detail retaining capacity and drawing precision of the model are improved. Furthermore, accurate identification and positioning of topological features are realized by adopting calculation of a cell complex sequence and a topological feature noise rank.

The invention discloses a PDF engineering drawing structured recognition method and device based on multi-dimensional feature fusion and a storage medium, and belongs to the technical field of engineering drawing intelligent processing. The method comprises the following steps: PDF analysis and preprocessing: analyzing a PDF engineering drawing file, extracting a vector graph drawing instruction, text block contents and respective original coordinate information, and carrying out image rendering and standardized preprocessing on a drawing page to generate a binary image with a standard resolution; multi-dimensional feature extraction: extracting the following four types of features from the binary image: a visual depth feature, a text semantic feature, an industry specific symbol feature and a spatial topology feature between elements; feature fusion and relation reasoning: inputting the visual depth features, the text semantic features, the industry specific symbol features and the spatial topological features into a graph neural network fusion module, and constructing a graph structure taking each identified element as a node and taking a spatial topological relation between the elements as an edge, performing feature interaction and fusion among nodes through an attention mechanism, and reasoning a semantic association relationship among drawing elements; and generating structured data: classifying and grouping the drawing elements according to the semantic association relationship, and outputting a structured data file according to a predefined structured format. Therefore, the technical problems of low recognition efficiency and accuracy in the prior art are solved, and the technical effect of efficient and accurate engineering drawing structured recognition is achieved.

An adaptive random access system and method with learned query optimization for compacted data files that enhances random access performance through machine learning and pattern recognition. The system incorporates a query pattern learning module that analyzes historical access patterns and user behavior to build statistical models of data usage. An adaptive estimator module improves location estimation accuracy by incorporating learned patterns rather than relying solely on mathematical calculations. A predictive boundary detector uses learned codeword patterns to more accurately identify boundaries in compacted data, reducing misalignment errors. An intelligent search engine coordinates optimization strategies including context-aware search string parsing and encoding strategy selection based on learned performance data. A dynamic codebook optimizer reorganizes sourceblock layout based on access frequencies and co-occurrence patterns to improve retrieval speed. An enhanced search cache implements predictive caching algorithms that anticipate user queries and proactively load relevant data.

Embodiments manage data in a file system over a network. A plurality of file system operations in the file system may be executed based on a file system client action or a file system administrative action such that the file system may be integrated with a network. Characteristics of the plurality network components in the network infrastructure that may be associated with the file system may be determined. Tests may be generated based on the characteristics of the network components such that the tests may be executed to evaluate the network components. Results of the tests may be employed to perform further actions, including determining non-compliant network components based on the results; modifying the network infrastructure based on the non-compliant network components such that one or more of file system operations are modified based on the non-compliant network devices; executing the modified file system operations on the modified network infrastructure.

The invention discloses a row-level data recovery method and device for a damaged file of a GoldenDB database, and the method comprises the following steps: S1, scanning a to-be-recovered GoldenDB data file, and recognizing and caching all data pages; s2, on the basis of metadata of the data pages, cluster index leaf node pages containing user data are screened out from the cached data pages; s3, for each screened leaf node page, analyzing an internal record organization structure of the leaf node page, and performing row-level data recovery; the row-level data recovery comprises the steps of traversing user records according to a virtual record pointer, and performing cross check and recovery on a traversal path in combination with a page directory slot so as to extract and mark the user records one by one; and S4, outputting all the recovered row-level data.

The invention provides a wafer test data processing method and device, equipment and a medium, and can be applied to the technical field of chips. The method comprises the following steps: acquiring a standard test data file generated when a wafer is tested; analyzing the standard test data file to obtain data files respectively corresponding to the plurality of data types; wherein the data file comprises test record data belonging to a corresponding data type; based on the data files corresponding to the multiple data types respectively, respectively generating analyzable data corresponding to each preset category in the multiple preset categories; and outputting the analyzable data corresponding to each preset category. According to the invention, automatic analysis and classification of the wafer test data are realized, and the efficiency is high.

The invention relates to a multi-agent cooperation system and method capable of realizing cross-domain mutual trust, and the system comprises a cross-domain mutual trust decentralized agent identity identification and verification system which is used for constructing an agent identity identification based on the decentralized identity of an agent and migrating the identity of the agent to the decentralized identity; the agent interaction information evidence storage system is used for performing hash anchoring on the data file of the agent, establishing a cross-agent task execution state consensus and generating interaction information evidence storage data of the agent; and the multi-agent cooperative task execution and dynamic access control system is used for executing interactive cooperation of task execution process control, dynamic access authority control and agent state management maintenance of multiple agents according to the task execution contract, the access control contract and the agent management contract. Therefore, the problems that cross-enterprise and cross-domain agent identity mutual trust cannot be established in the prior art, and serious limitation exists in the security and credibility level of the system are solved.

A system and method includes connecting an interface device to a port of a vehicle to be in communication with an electrical system of the vehicle for monitoring the vehicle, and running a selected one of multiple available calibration and / or repair programs via the interface device to generate a calibration / repair data file of the vehicle, where the data / log file is generated in one of a plurality of possible native file formats. A report generation tool acquires screen captures and / or screen recordings to document the data / information displayed during the steps of a calibration / repair procedure. An evaluation tool extracts calibration / repair data from the data / log file, where the evaluation tool is configured to extract calibration / repair diagnostic data from data / log files in each of the plurality of possible native file formats, and outputs the calibration / repair diagnostic data to a database in a common format from which detailed calibration / repair diagnostic reports are generated.

The invention relates to the technical field of power system monitoring, in particular to a power distribution terminal fault monitoring system and method. The dual-channel acquisition module is used for acquiring two analog quantities of a power distribution room and mapping the two analog quantities into a power grid environment characteristic matrix; the cyclic mapping module is used for carrying out decoupling operation and generating a noise separation feature vector; constructing a background noise dynamic reference based on the noise separation feature vector, and generating a judgment boundary threshold; performing cyclic increasing and resetting in the fault recall storage unit through a write-in pointer to form a terminal state data stream; the fault judgment module is used for comparing the amplitude of the noise separation feature vector with a judgment boundary threshold value and generating a fault locking instruction; and based on the fault locking instruction, generating a termination signal, freezing the write pointer, and extracting the partial discharge data file from the terminal state data stream. According to the method, a closed-loop monitoring system in which the environment self-adaptive reference and signal feature decoupling support each other is constructed, and a fault backtracking sample with time-space alignment and complete logic is provided.

In a blockchain, transacting a record comprises performing linear network coding on the record or on a data file corresponding to the record, to produce a plurality of coded data parts; and storing at least one of the plurality of coded data parts on the blockchain or storing a proof of knowledge on the blockchain, the proof of knowledge derived from the coded data parts. Linear network coding coefficients might be derived from cryptographic hashes of the plurality of coded data parts. An all-or-nothing transform can use the cryptographic hashes to provide the proof of knowledge.

The invention belongs to the technical field of data processing, and particularly discloses a GIS data intelligent conversion processing method and device, electronic equipment, a medium and a program product, and the method comprises the steps: receiving an SHP format data file, processing a file name code, and screening effective files; traversing the SHP file, converting the SHP file into a DWG format, and classifying and outputting the SHP file according to rules; processing the DWG file in batches based on a CAD filling algorithm of a transaction mechanism, generating a filling layer and executing entity filling; the DWG files are merged in batches through a file merging algorithm, and views are automatically adjusted; and compressing, packaging and returning the combined file. According to the method, the full-process automatic conversion from the SHP to the DWG is realized, the problems of coding disorder, incomplete data, complicated operation and the like in the traditional processing are solved, and the conversion efficiency and the result accuracy are improved.

The invention discloses a heterogeneous document structured data extraction system and method based on multi-modal fusion, and the method comprises the following steps: S1, receiving a heterogeneous document, and carrying out the preprocessing; s2, extracting visual and semantic modal information based on the visual backbone network and an OCR module, and fusing spatial coordinates, text content and layout features; s3, receiving a dynamic target mode Schema, executing field-level semantic matching, and calculating semantic similarity; s4, performing consistency verification, verifying and filling the field values, and correcting the associated fields; s5, converting the format into a data file in a specified format, and reserving fields to be mapped with an original document semantic block; s6, automatically switching a cloud mode and a local mode according to a deployment environment; and S7, outputting the data file of the target field. According to the method, high-precision and low-delay structured data extraction of the heterogeneous format document can be realized, and the automatic processing efficiency and the data credibility are improved.

Techniques for implementing a scalable automated training framework for anomaly and ransomware detection are disclosed. In some embodiments, a computer system performs operations comprising: instantiating a plurality of virtual machines, each one of the virtual machines being loaded with a corresponding file system; simulating user actions and ransomware on the virtual machines, the simulating of user actions and ransomware on the virtual machines causing changes to the corresponding file systems of the virtual machines; for each one of the plurality of virtual machines, generating a corresponding metadata file based on one or more corresponding snapshots of the virtual machine, the one or more corresponding snapshots indicating the changes to the corresponding file system of the virtual machine; and training a ransomware detection model using a machine learning algorithm and training data, the training data being based on the corresponding metadata files of the virtual machines.

According to the high-computing-power special processor architecture for the big data file and the processing method, a data preprocessing unit receives an original big data file and formats and cleans the original big data file, and a special acceleration computing chip executes a computing-intensive task and avoids the floating-point number precision problem; the parallel processing unit realizes parallel data processing through a MapReduce programming model, the cache storage architecture adopts a multi-level cache system and an LRU cache elimination algorithm to store an intermediate result, and the instruction set optimization module performs parallel operation on isomorphic continuous storage data. The method can be widely applied to multiple fields of data analysis, machine learning, high-performance calculation and the like, and has great significance in improving the data processing capacity in the big data era.

The invention relates to the technical field of embedded system construction, in particular to a software dependency relationship automatic integration method and system based on meta packaging, and the method comprises the steps: S1, creating a meta packaging framework in an embedded construction system, and defining and constructing a stage hook through a Makefile; s2, automatically deploying the pre-compiled software package and the shared dependency library to a target directory of a construction system through a resource injection script; s3, analyzing a metadata file of the pre-compiled software package, extracting dependency relationship information, and generating a global dependency relationship list based on a directed acyclic graph topological sorting algorithm; and S4, inversely writing the global dependency relationship list into the dependency declaration configuration of the meta-packaging by utilizing the dependency aggregation script. By implementing the scheme, the problems of dependency sequence disorder and metadata auditing failure during embedded system integration are solved, the reliability of system integration is improved, the system construction efficiency is optimized, the safety of system construction is enhanced, and the maintainability and expansibility of system construction are improved.

A ship sub-assembly weld seam identification method, comprising: creating a point cloud weld seam identification training dataset by means of point cloud discretization, virtual sampling, weld-zone semi-automatic interactive annotation, and style transfer-based augmentation of ship sub-assembly CAD data; training a point cloud weld seam identification model, and exporting a weld seam identification model data file; using a 3D point cloud camera array as a sampling camera to collect workpiece 3D point cloud data of a sub-assembly workpiece to be welded at the production site; by means of the weld seam identification model data file, obtaining weld seam annotation position data and positioning a weld seam; and issuing a welding process plan and instruction to control a welding robotic arm and a control device therefor to complete sub-assembly workpiece welding. Also provided are a ship sub-assembly weld seam identification system, a computer device, and a computer-readable storage medium. The method overcomes the shortcomings in conventional 3D weld seam identification methods such as point cloud incompleteness and identification failures caused by steel types and the imaging angles of 3D cameras, thereby greatly improving the adaptability of automatic weld seam identification methods to complex workpieces.

A method for digitizing image-based data includes receiving an image file including one or more target objects, generating an intermediate image by removing noise from the image file using a denoising machine learning model, identifying the one or more target objects included in the intermediate image using an object segmentation machine learning model, discretizing the one or more target objects that were identified using the trained object segmentation machine learning model, and storing the one or more target objects that were discretized in a data file, visualizing the one or more target objects, or both.

The invention discloses a kernel probe generation method and device, computer equipment and a storage medium, and relates to the technical field of operating system kernel monitoring, and the kernel probe generation method comprises the steps of obtaining a target metadata file corresponding to a current operating system kernel in response to a kernel probe generation request; determining a target declarative strategy file; and determining a target program logic file corresponding to the target declarative strategy file, and generating a probe code according to the target program logic file and the target metadata file to obtain a kernel probe program. The probe program source code adaptive to the current kernel version can be dynamically generated in combination with the target metadata file and the target declarative strategy file, kernel probe development logic and underlying kernel knowledge can be decoupled through the source code generation function, and developers do not need to deeply understand kernel internal data structures and version differences; the development threshold is lower, a specific operating system or probe type is supported, and a universal Linux kernel and multiple probe types are also supported.

Techniques for automated query response determination using a hybrid AI are disclosed herein. An example computer-implemented method includes receiving a data file and a request including at least one query associated with the data file and applying a hybrid model to the data file. Applying the hybrid model includes segmenting the data file into one or more portions, embedding the one or more portions into a vector space, extracting, from the data file, data associated with one or more classifications, storing (i) the embedded portions in a first database and (ii) the extracted data in a second database, and determining a response to request queries based on the embedded portions and the extracted data, wherein the hybrid model constrains each response based on a parametric input prompt associated with the extracted data. The example computer-implemented method further includes storing one or more data objects indicating each response.

The invention discloses a data processing method and device, a medium and a program product, and relates to the technical field of storage. Encoding the data to be stored according to the size of the data file; determining a target data hierarchy according to the data attribute of the to-be-stored data; determining a target data protection strategy corresponding to the target data hierarchy according to the data attribute of the target data hierarchy; according to the target data protection strategy, determining the number of data blocks and verification blocks needing to be written into the to-be-stored data; determining target storage nodes corresponding to the data blocks and the verification blocks according to the number of the data blocks and the verification blocks needing to be written in the to-be-stored data; and storing the coded data to be stored to the target storage node according to the target data hierarchy and the target data protection strategy. The utilization rate of the disk and the data read-write performance can be considered, the resource calculation overhead is reduced, and the file processing efficiency is improved.

Apparatus, method, and software of managing dependencies in branches. In an embodiment, a dependency manager is implemented on an automation tool communicatively coupled to a package registry that stores code packages comprising main packages and branch packages. The dependency manager is configured to expect a publish command at the automation tool to publish a branch package for a development branch of main code, identify a name of the development branch, and modify a scope in a metadata file of the branch package with the name of the development branch. In an embodiment, the dependency manager is configured to predict an install command at the automation tool to install one or more dependencies specified for the development branch, and modify each dependency in the metadata file to reference a published branch package corresponding with the dependency when a valid published branch package is found.

The invention relates to the field of traffic storage optimization and traffic data compression, in particular to a multithreading-combined lossless compression method for fine-grained traffic, which comprises the following steps of: acquiring a traffic data file, extracting a header triple based on the traffic data file, generating an identifier according to the header triple, and transmitting the identifier to a server; aggregating the traffic data files with the same identifier to obtain data streams, and generating a sorted data stream size table according to the data volume of the data streams; creating threads according to system computing power, distributing the data flow to the thread with the minimum thread load according to the data flow size table and the thread load condition, and outputting a data flow distribution scheme; and performing fine-grained characterization and serialization on each data stream to obtain an integer sequence and a byte sequence, selecting a compression processing method according to redundancy characteristics of the integer sequence and the byte sequence, obtaining a redundancy-eliminated sequence, and writing the redundancy-eliminated sequence into a compressed file. The invention aims to provide high compression efficiency to reduce the storage cost while ensuring the data precision.

The invention relates to the technical field of cloud storage, can be applied to business system platforms of financial science and technology, medical treatment and health and the like, and discloses a hierarchical storage method, device and equipment for data files and a medium, and the method comprises the following steps: acquiring the data files in a storage unit, and extracting data characteristic parameters in the data files; performing multi-dimensional quantitative analysis on the data feature parameters to obtain a dimensional feature analysis value; identifying a dynamic weight of the data feature parameter, and performing weighted calculation on the data feature parameter according to the dimension feature analysis value and the dynamic weight to obtain a dynamic storage analysis value; identifying a data storage type label according to the dynamic storage analysis value; matching the data storage type label with strategies in a storage strategy library to obtain a target storage strategy; determining a storage hierarchy according to the target storage strategy; a storage address of the data file in the storage hierarchy is identified and the data file is stored in the storage address. The accuracy of hierarchical storage of the data files can be improved.

The invention relates to the technical field of off-line data collection, and particularly discloses an off-line data collection method and system and terminal device.The method comprises the steps that information content to be collected is classified, and a standardized form template is configured; meanwhile, corresponding incidence relations between different information column categories in the form template are configured; exporting a corresponding form template according to the to-be-allocated user category and the corresponding permission; in response to an offline data file obtained after the user performs data collection on the respective form template, form rule verification and form format verification are performed respectively; splitting the form data information into an information column region, a data column region and a cell region, and performing rule verification on the information of each region; and for the data conforming to the verification rule, respectively organizing the data according to the divided regions, and storing the data to a background. According to the invention, efficient, reliable and flexibly-configured large-scale data acquisition and storage in an offline scene can be realized.

A computing system performs real-time replication of database management system transactions. The computing system includes a source DBMS, a replication service and a data lakehouse. The source DBMS stores at least one source transaction table recording at least one source transaction and generates at least one recovery log indicating at least one modification in the at least one source transaction table. The replication service replicates the at least one source transaction recorded in the at least one source transaction table by generating at least one data file having a first data format. The data lakehouse stores at least one lakehouse table corresponding to the at least one source transaction table and having a second data format different from the first data format, and to modify the at least one lakehouse table based on the at least one data file.