960 results about "File format" patented technology

Some embodiments of a method may include: obtaining Avatar JSON Interchange File (AJIF) data; decoding the AJIF data to generate avatar data; obtaining animation parameters from the avatar data; obtaining user movement data corresponding to a movement of a user; generating updated avatar data based on the user movement data; and sending the updated avatar data to a client device. For some embodiments, a method may include: generating Avatar JSON Interchange File (AJIF) data corresponding to an avatar; sending, to an application server, the AJIF data; obtaining user movement data corresponding to a movement of a user; sending, to the application server, the user movement data corresponding to the movement of the user; receiving, from the application server, scene update data, wherein the scene update data includes updated avatar data corresponding to the movement of the user; and rendering a scene update based on the scene update data.

The invention relates to a method and a device for generating software based on a large model technology, a medium and electronic equipment, and relates to the technical field of software generation, and the method comprises the following steps: acquiring demand information of a user for software generation; generating a configuration definition file corresponding to the large model generation demand information through a preset code, wherein the configuration definition file is a configuration file of a domain-specific language definition device; performing regular format reformatting processing on the configuration definition file to obtain a processed file; based on the processed file, determining a service flow logic corresponding to a service function in the to-be-generated software, and based on the service flow logic, generating a target software code corresponding to the to-be-generated software through a code generation large model, the format of the target software code being a configuration file format of the domain-specific language definition device; and based on the target software code, through a preset rendering engine, generating a front-end page and a rear-end page of the software needing to be generated. The method has the effect of improving the software development efficiency.

The invention discloses a small file distributed high-concurrency aggregation storage method and system, and the method comprises the steps: collecting performance index data, and transmitting the data to a resource coordination server; calculating a queuing rate; determining a target server according to the queuing rate, the file reading concurrency and the disk residual space; determining a first-level directory hash value; selecting a first-level storage directory and a second-level storage directory according to the first-level directory hash value; creating a target aggregation file in the secondary storage directory, generating a 2-byte file format field according to the compression identifier or the non-compression identifier, and generating a 4-byte file length field according to the size of the to-be-written file; writing the file format field, the file length field and the to-be-written file into a target aggregation file in sequence, and recording the initial offset of writing; and generating a file name containing the storage position information, and returning the file name to the client. According to the invention, the efficiency and effect of small file storage are optimized.

Providing unified storage for event streams in an anomaly detection framework, including: receiving, by an event streaming platform, first event data encoded in a first file format; converting, by the event streaming platform, the first event data into second event data encoded in a second file format for storage in a first remote storage system; and providing, to the first remote storage system, a command to load the second event data into the first remote storage system.

The invention discloses an SSD (Solid State Disk) testing method, which relates to the technical field of SSDs, and comprises the following steps: an SSD is connected to testing equipment, and the testing equipment comprises a controller, a data generation module, a data transmission module, a data storage module and a performance monitoring module; specific types of test data are generated through a data generation module, the specific types of test data comprise sequential read-write data, random read-write data and mixed read-write data, the file size of the sequential read-write data is within the range of 1GB-10GB, the operation block size of the random read-write data is within the range of 4KB-64KB, and the file size of the mixed read-write data is within the range of 4KB-64KB. The ratio of sequential read-write to random read-write in the mixed read-write data ranges from 1: 1 to 3: 1, the test data further comprises multiple file formats including but not limited to text files, image files, video files and audio files, and the data size of each file format accounts for 10%-30% of the total test data size; the SSD performance can be accurately evaluated, and the performance evaluation standard is perfected.

The invention provides a multi-class business data importing method and device, electronic equipment and a storage medium, and is suitable for the fields of financial science and technology and medical services. The method comprises the steps of obtaining a business data import request, a corresponding business data file and a target data table; analyzing the business data file to obtain a business file format, and determining a target analysis rule in a preset analysis rule base; performing field analysis on the business data file based on the target analysis rule to obtain multiple pieces of data field information; for each piece of data field information, matching the data field information with each piece of target field information to determine an import mapping relationship between each piece of data field information and the target field information; performing structured splitting on the business data file according to the target analysis rule to obtain structured business data; and importing the structured business data into the target data table according to the importing mapping relation. The method and the device can improve the efficiency of importing multiple types of business data into the database.

Methods and systems for generating a sharable model splice of a digital engineering (DE) model are provided. The method comprises receiving a DE model file in a native file format; extracting model data; storing the model data in a storage area; generating external, commonly-accessible splice functions that enable external access to digital artifacts derived from the model data; and generating the sharable model splice, which comprises access to a selective portion of the digital artifacts, and access to at least one of the splice functions. The splice functions provide addressable API or SDK endpoints that enable access by third-party applications and users to the digital artifacts without access to an entirety of the DE model file and without requiring direct engagement with a DE tool associated with the DE model type. These endpoints also provide a unified programming interface to sharable model splices generated from DE models.

The invention discloses an implementation method for generating a transformer substation BIM model by using a language based on an AI model, belongs to the technical field of BIM, and fills the blank of conversion from the language to the model: if a main transformer is located on the north side and is connected with a 110kV bus through a circuit breaker, the main transformer is directly converted into a compliant transformer BIM model; aiming at the existing family library of the transformer substation, realizing a searching function of an intelligent agent, accurately calling a searching tool according to parameters input by a user, and obtaining a corresponding equipment model file; and outputting a 3D model file, and strictly ensuring that the file format can be imported into the three-dimensional software (such as obj, fbx, glb and the like) of the Blog super-equal transformer substation for intercommunication.

The invention provides a file uploading attack interception method based on semantic entropy enhancement, and aims at overcoming the defects of an existing file uploading security protection technology in the face of complex attacks. The method specifically comprises the steps that S1, file format analysis and content extraction are conducted, hidden scripts are mined through nested content recognition, and intermediate representation is generated through grammar cleaning and coding specifications; s2, constructing an abstract syntax tree and semantic entropy calculation, tracking a pollution chain, analyzing a high-risk function, identifying a high-entropy character string, modeling and controlling flow complexity, and generating a semantic entropy vector; s3, dynamic scoring and decision making are carried out, and accurate judgment is carried out in combination with white list perception, feature comparison, multi-modal model scoring, adaptive threshold and sandbox observation; and S4, carrying out real-time interception and feature synchronization, blocking malicious file landing, generating an attack log and synchronizing an attack fingerprint. The method takes the semantic entropy vector as a core, breaks through the limitation of static features, remarkably improves the recognition rate of complex attacks, reduces missed judgment, and guarantees the safety of Web applications.

The invention provides a lightning proximity prediction method based on a space-time separation convolutional neural network. The method comprises the following steps: S1, acquiring satellite infrared brightness temperature observation data and lightning positioning data; s2, performing spatial resolution adjustment and standardization processing on the satellite infrared brightness temperature observation data; gridding and de-noising processing is carried out on the lightning positioning data; s3, defining a prediction task; s4, establishing a space-time sequence prediction model; based on the processed data, storing the processed data in a numpy file format according to a time point sequence, dividing the processed data into a training set, a verification set and a test set, and loading the training set, the verification set and the test set to a space-time sequence prediction model for model training to obtain an optimization model; and based on the prediction task, using the optimization model to carry out lightning approaching prediction to obtain lightning prediction data. According to the method, the development of cumulus cloud is captured by using satellite infrared brightness temperature observation data and brightness temperature difference data, so that the problem that thunder and lightning inception cannot be effectively predicted is solved.

Methods, systems, and bitstream syntax are described for a file container that supports the storage and transmission of multi-plane images. Examples are provided for coding texture and opacity information using HEVC or VVC coding and the HEIF container. Examples of carrying coded MPI images according to V3C and an example HEIF-based player are also presented.

The invention discloses a graphical user interface test case generation method based on a multi-agent framework, and relates to the field of graphical user interface tests.The graphical user interface test case generation method based on the multi-agent framework comprises the following steps that S1, a user demand document is obtained, and file text content and file format information are analyzed and extracted; s2, performing paragraph segmentation on the file text content to form logic semantic units; s3, carrying out correlation analysis on the segmented paragraphs, and obtaining a ternary file group; s4, performing paragraph annotation addition on the ternary file group, and constructing a semantic annotation result set; s5, extracting the agent framework to generate a graphical user interface test case, performing test recording, and storing a test result; s6, the result is verified, and a test case list and a software test report are generated. By conducting multi-dimensional analysis on the text content and the format structure in the document, the reduction efficiency from natural language description to structural semantic construction is improved.

The invention provides an automatic bidding and tendering file information extraction method and system based on a large language model, and the method is suitable for various file formats through preprocessing a bidding and tendering file; constructing a data set in the field of bidding and tendering documents, and performing fine adjustment on the BERT model based on the data set to realize rough labeling of the bidding and tendering documents; further performing fine adjustment on the generative large language model, and refining the rough label by using the context understanding capability of the generative large language model; the fine-tuned BERT model and the generative large language model are integrated into a dual-stage information extraction model, and automatic information extraction is realized, so that the accuracy and efficiency of extracting key information from bidding documents are effectively improved. In addition, the key information is output through highlight display and structuralization, so that the extraction result is visually presented to the user, and the practicability of the information is ensured.

A machine learning model is scanned to detect actual or potential threats. The threats can be detected before execution of the machine learning model or during an isolated execution environment. The threat detection may include performing a machine learning file format check, vulnerability check, tamper check, and stenography check. The machine learning model may also be monitored in an isolated environment during an execution or runtime session. After performing a scan, the system can generate a signature based on actual, potential, or absence of detected threats.

The invention relates to the technical field of natural language processing, in particular to an enterprise transformation diagnosis report generation method based on a large model. Collecting corpus data by using an enterprise diagnosis questionnaire; constructing a digital transformation diagnosis knowledge base, and storing the knowledge base into a vector database; training a sample model, and constructing a diagnosis report template through fine tuning of Prompt cue words; and taking the fine-tuned cue word as input, automatically generating a diagnosis report by utilizing the trained large model, selecting different file formats by utilizing an agent, generating a diagnosis report and outputting the diagnosis report. Through questionnaires and industry characteristic analysis, diagnosis suggestions are intelligently generated, enterprise transformation pain points are identified, and the efficiency and accuracy of enterprise transformation diagnosis are improved.

A system and method for compression performs analysis of incoming audio or video data, and selects a manifold based on the analysis of the data. A deep learning model is then trained for the manifold. The data is broken down into components and entropy maximization algorithms are utilized for each component before compression commences. Finally, the system translates the compressed data into a standard file format.

A system and method are provided for generating a cybersecurity behavioral graph from a log files and / or other telemetry data, which can be unstructured or semi-structured data. The log files are applied to a machine learning (ML) model (e.g., a large language model (LLM)) that generates / extract from the log files entities and relationships between said entities. The entities and relationships can be constrained using a cybersecurity ontology or schema to ensure that the results are meaningful to a cybersecurity context. A graph is then generated by mapping the extracted entities to nodes in the graph and the relationships to edges connecting nodes. To more efficiently extract the entities and relationships from the data file, an LLM is used to generate regular expressions for the format of the log files. Once generated, the regular expressions can rapidly parse the log files to extract the entities and relationships.

The invention relates to the technical field of file storage, and discloses a method and a system for storing multiple concurrent large files. According to the method and the system, the format and the size of a file are verified, a unique file name is generated and used for identifying metadata of a storage file and outputting the file, each small block of the file is divided into a fixed size and is divided into small blocks, a unique identifier is generated for each small block, a database is connected, and the metadata of the file is stored in the database. Then traversing each small block, selecting a storage node for each small block, uploading the small blocks by using multiple threads, setting a request queue, processing file uploading and downloading requests in sequence, avoiding concurrent write-in conflicts of the same file by using a lock mechanism for file uploading, and reading and controlling a read request through a read-write lock; and acquiring the information of the storage file from the database, acquiring each small block by utilizing a concurrent downloading mode, recombining the small blocks into an original file in sequence after downloading is completed, and performing integrity verification after file recombining.

A system and method for compression performs analysis of incoming audio or video data, and selects a manifold based on the analysis of the data. A deep learning model is then trained for the manifold. The data is broken down into components and entropy maximization algorithms are utilized for each component before compression commences. Finally, the system translates the compressed data into a standard file format.

Computer implemented systems and methods are disclosed for importing data from electronic data files. In accordance with some embodiments, a file format is assigned to a source electronic data files by a data importation system. The data importation system may further identify a file type identifier associated with the source electronic data file and map the source electronic data file to a transformation template. The data importation system may further store the file format, file type identifier, and an indication of the transformation template as a file type profile associated with the source electronic data file in a database.

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.

Methods and systems for generating a sharable model splice of a digital engineering (DE) model are provided. The method comprises receiving a DE model file in a native file format; extracting model data; storing the model data in a storage area; generating external, commonly-accessible splice functions that enable external access to digital artifacts derived from the model data; and generating the sharable model splice, which comprises access to a selective portion of the digital artifacts, and access to at least one of the splice functions. The splice functions provide addressable API or SDK endpoints that enable access by third-party applications and users to the digital artifacts without access to an entirety of the DE model file and without requiring direct engagement with a DE tool associated with the DE model type. These endpoints also provide a unified programming interface to sharable model splices generated from DE models.

The invention discloses a behavior tree code automatic generation method based on a large language model. The method comprises the following steps: 1, acquiring a behavior tree model of an XML file format defined by a user and prompt information input by the user; 2, analyzing the obtained XML file, and providing a generation rule of a behavior tree code; step 3; the analyzed XML file and prompt information input by a user are combined with a behavior tree code generation rule, and a task specific prompt is generated; 4, combining the task specific prompt with the general code generation prompt to generate a complete prompt; 5, a proper LLM is selected, complete prompt information is input, and the LLM generates codes according to prompts; 6, running the generated code in a safe environment to ensure the safety of the code and the correctness of an output format; and 7, displaying an execution result on a visual interface, auditing the result by a user, and modifying a generated code. The method has the characteristics of high universality, high flexibility and high interpretability.

The invention relates to the field of computer software, in particular to an IPFS-based file control method and device, equipment and a medium, and the method comprises the steps: receiving a file uploading request initiated by a user through a front-end interface; basic information of the file is read, a file format is confirmed, and the file format and a preset type list are verified; performing security and integrity verification on the files passing the verification; if the verification is passed, uploading the file to an IPFS network, and obtaining a hash string returned by the IPFS as a file identifier; constructing an encrypted access URL of the file based on the server address and the hash string, and storing file metadata to a database; and receiving a file access request initiated by a user through the URL, decrypting the URL and verifying the user permission, retrieving the file from the IPFS network according to the hash string, and providing a preview or download service according to the file type. And uploading of file types which do not meet requirements is effectively avoided, and potential safety risks are reduced.

The invention discloses a nuclear facility decommissioning simulation file editing management method based on cloud and local collaboration, and relates to the technical field of file management, and the method comprises the steps: verifying the identity of a user, receiving a file, and converting the file format; processing the simulation file through the first collaborative editing and performing real-time auditing; and setting a file operation authority based on the first encrypted storage file. According to the nuclear facility decommissioning simulation file editing management method based on cloud and local collaboration provided by the invention, intermediate format conversion is performed after the data is received, the applicability and flexibility of the system are improved, and the efficiency of multi-user operation is improved through a collaborative editing and auditing mechanism; and meanwhile, the correctness and consistency of the file are ensured in the aspect of processing conflicts, the security of the data is protected through encrypted storage and authority control, and higher security and recovery speed are achieved in the face of attack and decryption. The method has better effects in the aspects of safety, application range and reliability.

The invention discloses an AI large model-based public data classification and grading identification method, which comprises the following steps of: S1) pre-analyzing a supported file format by adopting a file analysis engine to form a classification and grading standard file; s2) the large model base adopts an enhanced retrieval generation process, and a data classification and grading database is established; s3) inputting an original data table and unstructured data, and completing initial data summarization of the large model; s4) adopting Few-Shot to learn successful classification cases memorized for a long time, and performing large model question and answer; and S5) based on all possible large model question and answer classification results, the large model engine performs automatic question and answer again, autonomous reflection is performed based on a first round of intelligent classification result, and a new data classification result and classification confidence are determined again. According to the method, the recognition accuracy can be greatly improved, and the problems of low accuracy, low efficiency, many human errors, poor adaptability and the like in a traditional data classification and grading method are solved.

The embodiment of the invention provides a virtual platform simulation monitoring method and device, and the method comprises the steps: carrying out the signal analysis of a received programmable logic controller signal of an actual production line through a set code analysis model, obtaining a corresponding virtual signal table, building a motion track of a simulation model in simulation software according to the virtual signal table, and carrying out the simulation monitoring of a virtual platform. A simulation event is added to the key control node; outputting a virtual production line model in a 3D model file format, and issuing the virtual production line model and the message queue connection parameters to a webpage end; after a ready state signal of the webpage end is monitored, starting to send position information and state change information of a virtual production line model to a message queue service, so that the webpage end updates a corresponding model position and a model state after receiving the position information and the state change information; according to the invention, the automation and real-time interactivity of simulation monitoring of the virtual platform can be effectively improved.

The invention discloses a method and a device for testing a diagnosis fault code of a controller area network, and relates to the technical field of automobile electronic diagnosis, and the method for testing the diagnosis fault code of the controller area network comprises the steps: obtaining a database file and test configuration information of the controller area network; generating message records of all verification messages according to the test configuration information and the controller local area network database file; sorting the message records according to time, and generating a message record file according to a preset file format; playing back the message recording file through a controller local area network tool, and sending a diagnosis request message to the tested controller through the controller local area network tool while playing back the data to obtain a diagnosis fault code; and comparing the diagnosis fault code with a preset expected diagnosis fault code to obtain a test result. According to the method, the automation degree and the real-time performance of the test are improved, the dependence on physical hardware and environmental resources is reduced, and the test cost and the technical threshold are reduced.

The invention provides a cross-platform collaborative loading method for CAD drawings, and relates to the technical field of data processing.The cross-platform collaborative loading method comprises the steps that rasterization layering processing is conducted on an original CAD file on a central platform, and a multi-stage grid tile set is obtained; storing to a temporary storage unit by adopting a pyramid hierarchical index; acquiring an updated view state by monitoring a user interaction event in real time, and comparing the updated view state with the original CAD file to obtain view parameters; extracting a target grid tile set; converting into a neutral exchange format set; according to the format support features, scheduling the container format conversion service, and compatibly distributing the container format conversion service to M edge platforms; and performing synchronous rendering replacement of the cross-platform tile file according to the M role permissions. The technical problems that in the prior art, due to the fact that effective CAD file format compatibility processing is lacked, tedious data conversion needs to be carried out among all platforms, and then the accuracy and reliability of data are reduced are solved.

The embodiment of the invention provides a file migration method, a storage medium and an electronic device, and the method comprises the steps that a target table is created according to basic information of a source table, and the source table and the target table support different stored file formats; under the condition that the file in the source table is migrated to the target table, a target conversion parameter value is determined in a target mapping relation according to the data size of the file to be migrated, and the corresponding relation between the data size of the file migrated within the historical time range and the conversion parameter value is recorded in the target mapping relation; and performing format conversion on a to-be-migrated file through the target conversion parameter value, and migrating the to-be-migrated file after format conversion to the target table. Therefore, the problem that the file cannot be automatically migrated due to different parameter settings required by file migration of each table in the related technology is solved, and the effect of improving the file migration efficiency is achieved.