40 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.

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 modules 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.

The disclosure presents systems and methods for hierarchical classification of input data across a plurality of categories. A machine learning model processes various data formats, starting with dimensional reduction using tokenization techniques, such as Bert-tiny tokenization, to create model-readable representations. The system predicts super-categories, sub-categories, and granular categories through selective activation of sub-layers tied to identified super-categories, optimizing computational efficiency. Label smoothing during training mitigates overconfidence in predictions, while softmax normalization refines inference outputs. Synthetic data generation using Large Language Models (LLMs) supplements training datasets, and an automated data labeling pipeline efficiently generates hierarchical labels. Modifications to the model, such as stop word removal and file size limitations, further reduce latency. Inference analyzes logits to predict hierarchical paths, providing detailed classifications with clear outputs. The method is adaptable for multimodal formats, ensuring scalable and accurate predictions across diverse data types while minimizing computational costs and improving reliability.

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.

The invention provides a method for realizing reversible conversion between a double-side bounded variable and an unbounded variable and a related product. The method comprises the following steps: valuing the double-side bounded variable; converting bounded variables on the two sides into unbounded variables; mathematical transformation of bounded variables and unbounded variables on the two sides is proved to be reversible; it is proved that functions at forward and reverse transformation segmentation points are continuous; and it is proved that first-order derivatives at forward and reverse transformation segmentation points are continuous. The method has the advantages that the bounded variables on the two sides of water transportation are converted into unbounded variables, and the problem that a Kalman filter, a steepest descent method, a DSRC method and the like are not suitable for the bounded variables on the two sides during data assimilation or mathematical model robust correction is solved. Compared with a traditional method of inserting an intermediate step in an algorithm and forcibly adjusting and correcting a result to return to a boundary condition, the method has the advantages that the basic assumptions of the peripheral nested algorithms are not damaged, the continuity and integrity of the algorithm are ensured, introduction of new errors which cannot be estimated and controlled is avoided, and the method is suitable for large-scale popularization and application. Theoretically, a data assimilation and model deviation correction model nested on the periphery can be more stable, and the assimilation and deviation correction effects are better.

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 a method for realizing reversible conversion between a water transport upper boundary variable and an unbounded variable and a related product. The method comprises the following steps: valuing an upper bounded variable; converting the upper bounded variable into an unbounded variable; mathematical transformation of bounded variables and unbounded variables is proved to be reversible; proving that the first-order derivative at the forward transformation segmentation point is continuous; and proving that the first-order derivative at the inverse transformation segmentation point is continuous. The method and the device provided by the invention have the beneficial effects that the conversion from the bounded variable of the water transport upper boundary to the unbounded variable is successfully realized. The conversion can meet the requirements of a part of mathematical assimilation methods and mathematical models for unbounded variables in the water transportation information processing and water transportation variable simulation and prediction processes. According to the method, the basic assumptions of the peripheral nested algorithms are not destroyed, the continuity of the algorithms is ensured, and the introduction of new errors is prevented. From the theoretical level, the assimilation precision of the peripheral nested data and the correction precision of the model correction model are higher, and the algorithm is more stable.

The invention discloses a user interface generation method and device and electronic equipment, and relates to the technical field of computers. The method comprises the steps that a data model corresponding to a user interface is created, the data model comprises a plurality of nested data sub-models, and each data sub-model comprises a row or a column of control data and an attribute indicating whether the control data is displayed or not; creating a view corresponding to the user interface, wherein the attributes of the view comprise at least one of the following: row height, column width, grid line attributes and an alignment mode of a control in a grid; and binding the view with the data model so as to carry out grid layout on each control in the user interface. According to the method, line and column display hiding and line height and column width setting can be realized without additionally writing codes, so that the interface development efficiency is improved. By setting the grid line attributes in the view attributes, the background styles of the grid lines and whether to display or not can be realized. Codes are high in readability, which row and which column a certain item is specifically located in a grid can be easily distinguished, and later maintenance is facilitated.

Methods, apparatus, and processor-readable storage media for processing transactions using nested data objects are provided herein. An example computer-implemented method includes: generating a nested data object corresponding to a file, where the nested data object includes a first layer for a first transaction related to the file; adding, for each of one or more additional transactions related to the file, a corresponding additional layer to the nested data object, where each layer of the nested data object include one or more respective hash values and one or more respective private keys; and transmitting the nested data object to a user device, where each layer of the nested object are encrypted based on a type of access specified for a user of the user device, and wherein each of the transactions is verifiable based at last in part on the one or more hash values of the corresponding layer.

A method comprises partitioning a data object into a sequence of nested data objects each including fragments having K symbols per fragment. The method further comprises processing the nested data objects to produce sequences of coded payloads corresponding to the nested data objects. The processing includes, for each nested data object: using (n, K) coding for which n>K, individually coding the fragments of the nested data object into codewords with n codeword symbols per codeword; and generating, from the codewords, a sequence of coded payloads that are unique for the nested data object. The method further comprises transmitting coded payloads of the sequences of coded payloads.

The embodiments of the present invention provide a method, apparatus, device and storage medium for determining part nesting data, which obtains the three-dimensional model data of the target part generated by a first application, and then determines the part attribute information and shape description information of the target part based on the three-dimensional model data, and determines whether the shape description information matches the nesting data conversion interface defined by the second application. If the shape description information cannot be directly used by the second application, the existing technology requires technicians to manually calculate, resulting in an inability to quickly convert the format of the shape description information of the target part; while the embodiments of the present invention can quickly obtain the shape description compatibility information of the target part through format conversion, and use the second application to process the part attribute information and shape description compatibility information to determine the nesting data of the target part. No human intervention is required, thereby shortening the time to generate nesting data and improving the efficiency of the nesting process.

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.

This application discloses a data processing method, apparatus, device, and medium. The method includes: when an integration platform obtains a data source to be stored, it verifies the data source to be stored. If it meets preset conditions, it persistently stores the data source to provide reliable data for subsequent business operations. Furthermore, the integration platform supports storing the data source to be stored in a nested data structure, thereby accommodating data of various complex structures and improving the diversity of business processing.

The invention belongs to the technical field of software testing, and relates to a multi-protocol self-adaptive intelligent assertion engine system and a cross-platform verification method. The system comprises a protocol sensing layer, a unified description layer, an adaptive execution layer and an intelligent analysis layer, the protocol perception layer comprises a protocol feature library, a multi-dimensional feature extractor, a confidence coefficient decision engine and a protocol version identification subunit; the unified description layer comprises a DAL grammar parser, an abstract syntax tree generator and a protocol independent verification rule converter; the adaptive execution layer comprises a verifier factory, a class loader isolation container, a protocol-verifier mapping table and an execution result aggregator; the intelligent analysis layer comprises a nested data comparison engine, a binary difference calculation unit, a multi-dimensional result correlation analyzer and a visual renderer. The protocol identification accuracy is high, and the code reuse rate is high; the maintenance cost is low; multi-dimensional verification is realized; the new protocol is short in adaptation period and high in expansion capability, and the data flow difference in the multi-protocol interaction link can be visually displayed.

1. The name of the design product: secondary nested data display graphical user interface of electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface content. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for the user to switch, view and compare each group of data and the management page of the secondary nested data proportion of each group of data; the front view displays the home page of the management page; the module located in the upper left part is a data comparison and viewing module, which is used to view two groups of data and can compare the two groups of data, wherein AAA1 is displayed by default in the front view; click "CCC1" below the "ABC-XXX" ring in the front view to switch to the interface change state diagram.

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 embodiment of the invention provides an operation method and device for a data object in a table and a storage medium, and relates to the technical field of data visualization. The first table has a first parallel data set and a first nested data set which correspond to each other; wherein the parallel data set represents the storage logic of each data item in the table, and the nested data set represents the display logic of each data item in the table; in response to a first operation on a first data object in the first table, updating the first parallel data set into a second parallel data set; the first data object comprises at least one data item; generating a second nested data set based on the second parallel data set; and refreshing and displaying the first table into a second table according to the second nested data set. When different operations are responded, the table can be directly displayed according to different requirements of a user no matter whether the data items need to be nested or not, and the flexibility and convenience of table operation are improved.

The invention discloses a data flattening method based on transition type breadth-first traversal, and relates to the technical field of computer software. Comprising the following steps: automatically generating and acquiring block configuration data of a current application scene, and converting multi-level nested data capable of being constructed into a tree structure into a plurality of block N-way trees; converting the plurality of block N-way trees into a plurality of N-way trees with specified flat levels through a transition type breadth-first traversal algorithm; and assembling the N-way trees of the specified flat hierarchy into flat data of the specified flat hierarchy. According to the method, the flattening method is packaged, the specified flat hierarchy configuration item is opened to be used by the user, the problem that a large number of codes need to be written during data flattening processing of the specified flat hierarchy in diversified scenes is solved, all data formats capable of being constructed into a tree structure are supported, meanwhile, the memory utilization efficiency and the processing speed are improved, and the user experience is improved. And the flexibility of configuration driving is realized.

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.