24 results about "Nested data" patented technology

The invention belongs to the field of data processing, and particularly discloses a method and system for automatically generating a document according to a template and structured data, and the method comprises the steps: processing an archive template file according to a document object model analysis method, extracting the position, the type and the associated tag of a placeholder, and obtaining a placeholder metadata set; according to the placeholder metadata set, traversing a document hierarchical nesting relationship by adopting a depth-first search algorithm to obtain a hierarchical placeholder mapping table; obtaining the structured data of the document repair record through an external data source, judging whether the structured data field corresponds to the tag in the mapping table according to the hierarchical placeholder mapping table, and if so, generating a matching pair list from the field to the placeholder to obtain a preliminary matching data set; the objective of the invention is to solve the problem of a business scene in which complex nested data and file template placeholders cannot be accurately matched in a document repair record in the prior art.

The invention is suitable for the technical field of chips, and particularly relates to a modeling method and system for chip layout planning and related equipment.The method comprises the steps that configuration information of a chip is obtained, and a configuration file is established according to the configuration information; storing the module information in a module corresponding to the module list; establishing a multi-level nested data structure according to the module relation data; performing coordinate calculation and merging on modules of different levels in the nested data structure to obtain module coordinate data with coordinate information of all the modules; and performing shape drawing according to the module coordinate data to obtain a chip layout model. Compared with the prior art, the method has the advantages that real-time iteration can be performed according to the actual progress of chip design, designers are greatly facilitated to deeply think the chip architecture design, more accurately estimate the layout area and better determine the distribution position of the module, and the design efficiency is improved. Therefore, excessive dependence of top layer layout planning work on a traditional EDA tool is eliminated.

Techniques for transforming code modules to different programming languages are disclosed. A system accesses a first non-code representation of a first code module expressed in a first programming language and parses the first non-code representation to identify a nested data element of the first non-code representation that represents a nested expression of the first code module. The system executes a transformation technique to transform the nested data element, in the first non-code representation, to a first non-nested data element in the first non-code representation. The system modifies the first non-code representation based on one or more attributes of a second programming language to generate a second non-code representation suitable for representing code modules in the second programming language. The system generates a second code module based at least on the second non-code representation.

The invention discloses a hierarchical nested data encryption method supporting fine-grained access control, which relates to the technical field of data security, and comprises the following steps: generating a master key; receiving to-be-encrypted user data, and performing data classification on the to-be-encrypted user data through the data classifier according to a predefined privacy sensitivity strategy to obtain a hierarchical data set; deriving a first-layer key from the master key, and carrying out authentication encryption on first-layer data in the hierarchical data set by using the first-layer key to obtain a first-layer ciphertext; and cooperatively deriving a current-layer key based on the previous-layer ciphertext, the previous-layer key and the hierarchical data set, carrying out byte connection operation on the previous-layer ciphertext and the current-layer data, and executing to-be-authenticated encryption layer by layer through authentication encryption band associated data in combination with the current-layer key to obtain a final nested ciphertext. According to the method, fine-grained access control layered according to data sensitivity is realized, and the risk of core sensitive information leakage is effectively reduced.

This application discloses a data parsing method, device, and medium for grassroots jurisdiction, belonging to the field of data governance technology. It addresses the problem of low data parsing efficiency. The method includes: determining the grassroots jurisdiction of a grid worker; receiving a grassroots data query request from the grid worker and verifying the grid worker's identity; if the grid worker passes authentication, invoking a brute-force recursive method; based on a preset grassroots database, performing nested data parsing on the grassroots jurisdiction using the brute-force recursive method to generate multi-level nested target grassroots data for the grassroots jurisdiction; and displaying the target grassroots data to the grid worker. This improves the data parsing efficiency for grassroots jurisdictions.

The present disclosure relates to methods, apparatuses, and readable storage media that implement serialization and deserialization of nested data, where a system-on-a-chip of the present disclosure is included in an integrated circuit apparatus that includes a general purpose interconnect interface and other processing apparatuses. A computing apparatus interacts with the other processing apparatuses to collectively complete a user-specified computing operation. The integrated circuit apparatus can also include a storage apparatus connected to the computing apparatus and the other processing apparatuses, respectively, for data storage of the computing apparatus and the other processing apparatuses.

This invention discloses a spatial downscaling method for weather forecast models based on a terrain classification super-resolution model. The method first obtains nested data at each layer through dynamic downscaling of the weather forecast model, then trains a super-resolution model using data at different resolutions of the target area. Following the above process, super-resolution models are established for different terrains, and a terrain classification model is trained using terrain data. The super-resolution model and the terrain classification model are combined to obtain a fused prediction result. This fused model is the SRBTC model, which considers spatial correlation. The model outputs the similarity probability between the area to be predicted and various different terrains. The prediction results are weighted and summed to obtain the fused prediction result of the super-resolution model. During model training, a specified value scaling method is proposed to consider the differences between high- and low-resolution meteorological simulation data. When applying the model, a splitting and merging method is proposed to consider the differences between multi-scale simulation data, and the applicability of the model is specified.

Improving the accuracy of detectable error rates on links between two network nodes involves transmitting IP-in-IP encapsulated test packets back and forth between the two network nodes. These test packets consist of a series of nested data packets with alternating destinations between the two network nodes. Transmitting these test packets on the network's data plane improves the accuracy of the detectable error rate.

The invention provides an interaction method and device supporting infinite nesting data structure visualization, and relates to the technical field of data structure visualization and man-machine interaction collaborative modeling. The method comprises the steps that recursive rendering of type perception is executed in response to a data structure loading event, and a nested graph with a clear hierarchical topology is generated; providing a double-input mode of an expression mode and a fixed value mode for basic type nodes, and realizing accurate binding of array variables through a special binding button, an intelligent array selector and a node type label identification and single-selection constraint mechanism under the expression mode; and starting a double-layer recursive verification process driven by a root node during submitting, and performing upward aggregation propagation and visual feedback on a verification result along a parent path. According to the method, the rendering performance and interactive user experience of the deep nested data structure are improved, real-time infinite recursion operation is supported, and the problems that topology is not visual, binding is prone to errors, verification is low in efficiency and the like in complex data structure visualization of a traditional tool are effectively solved.

The invention discloses a test report intelligent reading method, device and equipment based on a large language model and a storage medium, and belongs to the technical field of electric power, and the method comprises the steps: obtaining report specifications, topological structures and test item features of a power transformer test report; determining necessary items of the test report according to report specifications; determining association parameters associated with each necessary item according to the topological structure; determining a nested data structure of the test report according to the test item features; constructing a large language model according to the necessary items, the associated parameters and the nested data structure; receiving a report reading instruction, and determining a to-be-read test report according to the report reading instruction; extracting an original analysis text of the test report to be read; and inputting the report reading instruction and the original analysis text into the large language model, so that the large language model outputs standardized reading data of the test report to be read. According to the invention, the problem of low reading accuracy of the test report of the power transformer in the prior art can be solved.

The invention relates to the technical field of data processing, and provides a data processing method and equipment. The method comprises the following steps: collecting multi-type bus interface data on an aircraft; transcoding the multi-type bus interface data to obtain standard format data which can be identified by new avionics equipment; the data in the standard format is nested data in a type-length-data (Type-Length-Data) format; packaging the standard format data to obtain an Ethernet message; and outputting the Ethernet message to the new avionics equipment. According to the data processing method and equipment provided by the invention, the new avionics equipment can extract various types of bus data with various coding standards on the aircraft only by developing a unified data interface with the same coding standard during transcoding, so that the software and hardware development and maintenance process of the new avionics equipment is greatly simplified.

The invention discloses a two-dimensional layout algorithm selection method and system based on machine learning, and the method comprises the following steps: constructing and training an XGBoost model and a full-connection neural network model, and building a two-dimensional layout algorithm library; acquiring real-time layout data, extracting features and calculating feature values, inputting the features into an XGBoost model to obtain the selection probability of each algorithm, and screening out candidate algorithm sequences exceeding a preset probability threshold; the candidate algorithms are sequenced according to whether time factors need to be considered or not, calling and solving are conducted in sequence, if yes, the final algorithm is determined, and if not, subsequent algorithms are tried in sequence; and if all failures occur, inputting the characteristic values into the full-connection neural network to generate first n optimal algorithms, and forming a new sequence for reordering and solving. According to the method, the problem that in a two-dimensional layout algorithm selection method depending on artificial experience or a trial and error method, the artificial experience may cause subjective deviation, so that the accuracy and optimality of algorithm selection are affected is solved; and a trial-and-error method is easy to introduce a large amount of invalid calculation, so that the algorithm selection efficiency is low.

The application is suitable for the chip technical field, and particularly relates to a chip layout planning modeling method and system and related equipment, the method comprises the following steps: obtaining configuration information of a chip, and establishing a configuration file according to the configuration information; saving module information into a module corresponding to a module list; establishing a multi-level nested data structure according to module relationship data; performing coordinate calculation and merging on modules of different levels in the nested data structure to obtain module coordinate data with coordinate information of all modules; performing shape drawing according to the module coordinate data to obtain a chip layout model. Compared with the prior art, the application can be iterated in real time according to the actual progress of chip design, greatly facilitating designers to deeply think about chip architecture design, more accurately estimate the layout area, and better determine the distribution position of the module, so that the over-reliance of top layout planning work on traditional EDA tools is eliminated.

The invention relates to the technical field of data processing, in particular to a public satisfaction influence factor screening method, which comprises the following steps: acquiring public satisfaction monitoring data; preprocessing the public satisfaction monitoring data to obtain target analysis data; determining an independent variable index and a control variable index; and based on the independent variable index and the control variable index, adopting an HLM multilayer linear regression model to screen the target analysis data so as to obtain influence factors of the public satisfaction. Aiming at the problems that as the public satisfaction is used as hierarchical nested data, influence factors of the public satisfaction cover multiple levels of individuals, places and countries, the crowd satisfaction in the same place is not independent, and a classical regression method cannot be used for analysis, an HLM method is adopted for regression analysis, the influence factors are screened, and contribution of each level of factors to the public satisfaction is recognized; false positive results and key influence factors are effectively prevented from being missed, and an accurate analysis scheme is provided for public satisfaction influence factor research.

The invention discloses a data flattening processing method, a dynamic data verification method, equipment and a medium. The method comprises the following steps: performing recursive traversal on multi-layer nested JSON (JavaScript Object Notation) data; when the object type is traversed, splicing the parent path and the current key name to form a new path; when the array type is traversed, expansion is carried out by an index or an identifier; when a basic type is traversed, taking a complete path as a key and taking a value as corresponding content, and storing into a result set; in the data recursive traversal process, the context hierarchical relation of data is reserved, and single-layer key value pair mapping is generated. JSON data of a multi-level nested structure is expanded into a path type key value pair structure in a recursive mode, flattening processing of the data is achieved, efficient processing of complex nested data is achieved through the flattening processing method, the context relation of the data is reserved, meanwhile, the positioning and data verification logic of complex fields is greatly simplified, and the data verification efficiency is improved. The problems that the data verification logic rule is complex and the execution efficiency is low are well solved.

A system for delivering contextual responses through dynamic integrations of digital information repositories with inquiries, comprising a computing device configured to collect a plurality of inquiries associated with an entity, access a plurality of digital information repositories in communication with the at least a processor to retrieve a plurality of entity records pertaining to the entity, extract one or more entity features from the plurality of inquiries and the plurality of entity records, implement a nested data storage structure to store the plurality of inquiries and the plurality of entity records based on the one or more entity features, generate, at one or more process models interfaced with the computing device, one or more contextual responses upon receipt of an additional inquiry by traversing the nested data storage structure, and display the one or more contextual responses to the entity through a user interface at a display device.

This invention belongs to the field of software testing technology and relates to a multi-protocol self-adaptive intelligent assertion engine system and a cross-platform verification method. The system includes a protocol awareness layer, a unified description layer, an adaptation execution layer, and an intelligent analysis layer. The protocol awareness layer includes a protocol feature library, a multi-dimensional feature extractor, a confidence decision engine, and a protocol version identification subunit. The unified description layer includes a DAL syntax parser, an abstract syntax tree generator, and a protocol-independent verification rule converter. The adaptation execution layer includes a validator factory, a class loader isolation container, a protocol-validator mapping table, and an execution result aggregator. The intelligent analysis layer includes a nested data comparison engine, a binary difference calculation unit, a multi-dimensional result correlation analyzer, and a visualization renderer. This invention features high protocol recognition accuracy, high code reusability, low maintenance costs, multi-dimensional verification, short new protocol adaptation cycle, strong scalability, and the ability to intuitively display data flow differences in multi-protocol interaction links.

The application discloses a layered nested data encryption method supporting fine-grained access control and relates to the technical field of data security, and comprises the following steps: generating a master key; receiving user data to be encrypted, performing data classification on the user data to be encrypted according to a predefined privacy sensitivity strategy through a data classifier, and obtaining a hierarchical data set; deriving a first layer key from the master key, and performing authenticated encryption on first level data in the hierarchical data set by using the first layer key to obtain first layer ciphertext; based on the previous layer ciphertext and the previous layer key, the current layer key is derived in cooperation with the hierarchical data set, and the previous layer ciphertext is subjected to byte connection operation with the current level data, and the current layer key is combined to perform authenticated encryption on the associated data layer by layer to obtain the final nested ciphertext. The application realizes fine-grained access control according to the data sensitivity layering, and effectively reduces the risk of core sensitive information leakage.

The invention provides a full-automatic nesting method, system, medium and equipment, and belongs to the technical field of panel production process control. The method comprises the steps that a nesting task issued by a central control system is received; downloading a GEN file from an FTP server according to the nesting task, and generating nesting information according to the GEN file; and the nesting information is uploaded to the FTP server and sent to the central control system. The method can support real-time receiving of task information and transmission of trepanning data, supports various parts and multiple plates, and performs full-automatic overall trepanning, so that the cost is saved, the downtime is shortened, the safety is high, and the method is suitable for various advanced numerical control equipment.

The invention relates to the technical field of database system integration, and provides a contract data multi-system bidirectional synchronization and field mapping method and device.The contract data multi-system bidirectional synchronization and field mapping method comprises the steps that fields of different systems are named and standardized by building and loading a static field mapping table, and contract main table data in a source system and extended data model information of the contract main table data are obtained according to query conditions; performing field name conversion and value formatting on the acquired data according to a static field mapping table, and performing recursive processing and change tracking on a contract signing party sub-table and a money return plan sub-table associated with a contract; identifying field-level and sub-table-level change information by comparing historical versions of the contract data, and generating a structured change record; and assembling and synchronizing the converted main table data, the processed sub-table data and the change record according to a data structure of the target system. According to the method, the integrated development and long-term maintenance cost of the system can be remarkably reduced, and accurate synchronization of a complex nested data structure is completely supported.

A system and method for compiling and processing nested datasets within a state-based data model representing system entities. Each system entity is represented by a row in a two-dimensional state dataset, and related entities are identified across one or more state datasets. For a given system entity, a set of nested datasets is compiled using attribute values from its related entities. These nested datasets may include a nested process dataset comprising sequential or conditional instructions, nested query definitions for dynamic data retrieval, and nested view definitions for layout or visualization. The compiled entity structure can be processed locally or distributed to remote processors as part of one or more messages. The invention enables flexible, rules-driven orchestration of services and workflows and supports autonomous or semi-autonomous execution frameworks in AI, digital twin, or business process automation contexts.

This invention provides a method and apparatus for secure isolation of design data supporting regional collaborative development, relating to the technical field of data processing. The method includes: acquiring design data from different plants and institutes and binding them with data security region identifiers; constructing a multi-layered nested data security region structure and generating a set of cross-regional collaborative constraint rules; performing structural pruning, parameter mapping, and semantic dimensionality reduction on the design object data during cross-regional calls to form a restricted data expression set; constructing a cross-regional controlled data view based on the restricted data expression set and combining it with stage status identifiers to achieve dynamic control of the shared scope; simultaneously forming a data flow record set through call path resolution and binding with responsible entities; and performing abnormal access detection and adaptive policy adjustment based on the data flow record set and constraint rule set to update access boundaries and restricted data expression rules, and outputting collaborative design results. This invention can improve collaborative R&D efficiency while ensuring data security.

The invention discloses a Python-based river channel large section extraction method and system, electronic equipment and a storage medium, and relates to the field of flood routing numerical simulation. The method comprises the following steps: acquiring multi-source original topographic data of a target area, a river section, stake mark mileage and other files in a dwg format; carrying out vector multiple length processing on the unexpected large section of the river channel through a Python script, and carrying out self-adaptive equipartition so as to complement control points; elevation values are given to the control points by adopting four terrain adaptive algorithms, and a distance-elevation double-layer nested data list is generated; hydrological consistency verification is carried out through multi-dimensional detection, a stake mark-distance-elevation three-layer nested data list is constructed, and real-time early warning is carried out on abnormal data; and finally generating structured data and supporting multi-dimensional indexes. According to the method, through automatic preprocessing, self-adaptive elevation assignment and intelligent anomaly detection, the problems of low extraction efficiency and poor accuracy when the actually measured data quality is uneven are solved, and the supporting capacity of the large-section data of the river channel on the hydrological hydrodynamic model is improved.