47 results about "Structure type" patented technology

The invention relates to the technical field of underground power tunnel design data processing, in particular to an automatic reinforcement design method based on an instantiation reference algorithm, which comprises the following steps: constructing a multi-level parameterized model, orthogonally classifying structure types and shapes, and associating geometric features, mechanical attributes and reinforcement rules for each type of structure to form a structured database. A geometric boundary of the special-shaped structure is defined by adopting a B spline curve or an NURBS curved surface, and dynamic association with a reinforcement rule base is achieved through a topological relation mapping module. The instantiation reference algorithm calls a reinforcement template library according to load conditions, and optimizes the diameter, spacing and reinforcement ratio of reinforcements in combination with an elastic mechanics principle to generate an initial scheme. And generating a standard drawing and a synchronous statistical table through a CAD conversion model. According to the method, diversified special-shaped structure reinforcement design is supported, and a whole-process closed loop of parametric modeling, dynamic rule expansion and construction data delivery is realized.

The invention discloses a data backup method and system based on a multi-dimensional structure. The method comprises the steps of obtaining target data to be backed up and corresponding data source information; based on a data structure analysis algorithm, determining a plurality of structure data parts corresponding to the target data and corresponding structure types; according to the data source information, determining a backup priority corresponding to each structure type; and according to the backup priority and the structural data parts, determining a backup position and a backup sequence of each structural data part when the target data is backed up to a target server. It can be seen that accurate backup management based on the multi-dimensional data structure and source can be achieved, the data backup efficiency and safety are improved, and the data loss risk is reduced.

The invention discloses an optical metasurface structure parameter design model training and application method and a related device, and relates to the technical field of nanometer photonics nanometer structure design, the method comprises the following steps: obtaining a data set, the data set comprises multiple groups of sample data of each optical metasurface in a plurality of optical metasurfaces, the sample data comprises a sample structure name, a sample structure parameter and a sample spectral response, word embedding and position code embedding are respectively carried out on the sample structure name and the sample structure parameter to obtain an embedded sample structure name and an embedded sample structure parameter, a feature extractor is further utilized to extract and obtain a fusion feature, and the fusion feature is extracted to obtain a fusion result; and taking the fusion features as input, generating an embedded sample structure parameter predicted value by using a structure parameter generator, subsequently calculating total loss, and performing iterative updating based on the total loss until training is completed. The method can be suitable for design of structure parameters of optical metasurface of different structure types and different spectral targets, and generalization ability is improved.

The embodiment of the invention provides a chip layout image processing method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a basic structure type corresponding to a target graph according to the line segment position information in an obtained chip layout image; and determining a refined structure type corresponding to the target graph according to the line segment position information and the line segment angle information. And performing rule inspection on the target graph based on standard structure parameters preset for the refined structure type. The defect that only a graph parallel to the transverse axis direction or the longitudinal axis direction of a two-dimensional rectangular plane coordinate system or a graph with a specific bevel edge angle can be recognized at the present stage is effectively overcome and solved, and then the inspection precision and the inspection efficiency of design rule inspection or mask rule inspection are remarkably improved. The practicability and reliability of the rule checking process and the subsequent image adjusting process for the target graph are improved to a certain extent, so that the performance and the yield of the finally produced chip are powerfully guaranteed.

The invention discloses a micro-nano structure optical filter reverse design method based on deep learning. The method comprises the following steps: data preprocessing and data set construction; building a reverse design network model based on deep learning; jointly training the reverse design network to obtain a high-performance model; structural information of the optical filter is derived from the target transmission spectrum, and reverse design of the micro-nano structure optical filter is achieved. According to the micro-nano structure optical filter reverse design method based on deep learning, structure type classification and structure parameter regression are combined, batch processing of multiple micro-nano structures is supported, the limitation that an existing method only aims at a single structure type (such as a metasurface grating or a hole digging structure) is solved, and the method is suitable for large-scale popularization and application. And the universality and the application range of the reverse design are improved.

The invention discloses a medium and small span bridge modeling method based on an adaptive rule and a parameterized template, which comprises the following steps: splitting a bridge structure into a standard component and an adaptive component according to the type of the bridge structure, establishing a parameterized model library of the standard component, and setting parameter linkage and constraint among the components in combination with route topographic data, and generating a standard component model, on the basis of the standard component model, automatically calculating and fitting the physical dimension of the component at the missing part, and refining to generate a self-adaptive component model, thereby completing full-bridge three-dimensional high-precision modeling. By means of the mode, the defect that in the traditional parametric modeling process, parameter input and output are mainly manual work is overcome, full-process parametric driving design of engineering data-component design-model assembly is achieved, and the technical problem that under a complex curve route, the modeling precision of a small and medium-span bridge parametric model base is insufficient is solved; the linkage between bridge parametric modeling components is improved, input of repeated parameters in the model is effectively reduced, and the modeling efficiency is improved.

The present invention relates to the technical field of underground power tunnel design data processing, and in particular to an automatic reinforcement design method based on an instantiation reference algorithm. By constructing a multi-level parametric model, the structure type and shape are orthogonally classified, and geometric features, mechanical properties and reinforcement rules are associated with each type of structure to form a structured database. The special-shaped structure uses B-spline curves or NURBS surfaces to define the geometric boundaries, and is dynamically associated with the reinforcement rule library through a topological relationship mapping module. The instantiation reference algorithm calls the reinforcement template library according to the load conditions, and optimizes the steel bar diameter, spacing and reinforcement ratio in combination with the principles of elastic mechanics to generate an initial scheme. Standard drawings and synchronous statistical tables are generated by CAD conversion models. The present invention supports the design of reinforcement for diversified special-shaped structures, and realizes a full-process closed loop of parametric modeling, dynamic rule expansion and construction data delivery.

The subject technology receives a query, the query referencing a unified representation for structured type data and semi-structured type data, the unified representation being provided in storage and in memory during query processing, the unified representation comprising a set of structured type fields that include a set of semi-structured typed fields that enables type safety and enforcement for the set of structured type fields, and flexibility for the set of semi-structured typed fields in a same column, the unified representation in storage including type information for the semi-structured type data as part of the semi-structured type data, the unified representation being utilized for structured type data and semi-structured type data. The subject technology processes the query using the unified representation stored in the memory, the unified representation providing performance parity between structured type data and semi-structured type data.

The invention discloses a method and a device for structure optimization in three-dimensional digital-analog design. The method comprises the following steps: performing type identification on a three-dimensional mathematical model to be analyzed, and classifying structures in the three-dimensional mathematical model based on a result of the type identification to obtain different structure types; based on the different structure types, performing partition processing on the three-dimensional digital analog to divide the three-dimensional digital analog into a plurality of to-be-detected intervals, and performing interference detection on the plurality of to-be-detected intervals to obtain interference position data, each to-be-detected interval comprising a structure as an interference detection object; and respectively performing interference analysis on a plurality of interference detection objects corresponding to the interference position data, and automatically adjusting a corresponding structure in the three-dimensional digital model based on the result of the interference analysis. According to the invention, the technical problems of low efficiency and poor precision caused by the fact that interference detection depends on artificial experience in the existing clamp design are solved.

The embodiment of the invention discloses a data processing method, device and equipment, and the method comprises the steps: obtaining a plurality of different structural text data which can be decomposed into a plurality of different levels or substructures with position dependence; performing structural disassembly processing on each piece of structural text data to obtain a structural node corresponding to each piece of structural text data, and performing word segmentation processing on each structural node; for each segmented word, determining each segmented word and a corresponding context neighborhood, and further respectively determining semantic significance information between each segmented word and the corresponding context neighborhood, local contrast loss information corresponding to each segmented word and a boundary sparsification factor corresponding to each segmented word; further determining semantic anomaly significance information corresponding to each segmented word; and determining generalizable white list information and / or abnormal structural text data from a plurality of different structural text data based on the determined semantic anomaly significance information.

The embodiments of the present application provide a method, device, electronic device, and storage medium for scanning GraphQL vulnerabilities, wherein the method comprises: obtaining a GraphQL structure file; parsing the structure file to obtain a set of structure types for the GraphQL; constructing a request body according to the set of structure types; constructing a request according to the request body to obtain a GraphQL request; replacing the GraphQL request to obtain a replaced GraphQL request; and performing a vulnerability scan based on the replaced GraphQL request to obtain a response result. Implementing the embodiments of the present application can achieve automated scanning, improve the detection rate of GraphQL vulnerability scanning, quickly and accurately determine whether there are vulnerabilities in GraphQL, and simplify the scanning process.

The invention relates to the field of material science, in particular to a method for preparing a machine learning potential crystal structure training data set in a multi-source mode, and the method comprises the steps: S1, generating first-class training data of a specified structure type of a crystal through employing a Rose equation; s2, based on the experimental data, generating second-class training data of the pressure of the crystal structure changing along with the volume; s3, a representative configuration of the crystal is generated by using a traditional potential function, and single-point energy calculation is performed through a first principle to obtain third-class training data; and S4, based on the training data obtained in the steps S1, S2 and S3, further adopting a first principle to expand and perfect the training data, and finally generating a crystal structure data set. The training data is prepared in a multi-source mode, the Rose equation, the experimental data and the traditional potential function are combined with the first principle calculation, and compared with a method completely depending on the first principle calculation, the calculation cost of training data generation is greatly reduced, and meanwhile the data generation efficiency is remarkably improved.

The invention discloses a financial question analysis method and device based on a large language model, equipment and a medium, and relates to the technical field of natural language processing, and the method comprises the steps: retrieving a target sub-graph corresponding to a to-be-analyzed financial question from a knowledge graph, and carrying out the topology analysis of the target sub-graph, so as to obtain a structural representation vector; determining a graph structure type by using the structure representation vector, and determining a cue word template based on the graph structure type; determining priorities corresponding to the nodes on the basis of semantic relevancy and time relevancy between the nodes in the target sub-graph and the financial problem to be analyzed and PageRank scores of the nodes, sorting and recombining the nodes according to the priorities to obtain a target logic flow, and filling the cue word template by using the target logic flow to obtain a cue word template; obtaining a target prompt word; and inputting the target cue word into the large language model so as to generate an analysis result. A structural representation vector is obtained through topology analysis, and the problem of confusion of context organization of a generated result is solved.

The invention discloses a safe function parameter transmission method based on static binding of a hierarchical structure body and an RAM (random access memory), which belongs to the field of embedded system software design and comprises the following steps: S1, constructing a hierarchical function special structure body type with verification parameters; s2, function parameter transfer optimization; s3, realizing data and code life cycle synchronous management through compiler instruction and link script forced binding; s4, through an XOR verification mechanism, improving the function parameter transfer security; by constructing a three-layer function proprietary structure type with verification parameters, optimizing memory layout, eliminating memory holes and adopting an XOR verification mechanism, the security and high efficiency of parameter transmission are ensured, and meanwhile, synchronous management of data and code life cycles is realized through compiler instructions and link scripts, so that the security and high efficiency of data transmission are improved. The fragmentation problem caused by dynamic memory allocation is avoided, and the stability and reliability of the system are further improved.

The application provides a method and device for structuring thread steel data based on a laser point cloud, and the method comprises the following steps: obtaining a three-dimensional structure point cloud of thread steel; unfolding the three-dimensional structure point cloud to obtain an unfolded point cloud; generating an unfolded depth map of thread steel through the unfolded point cloud; identifying the unfolded depth map to obtain the positions of different structures in the unfolded depth map; and obtaining a plurality of groups of point clouds from the three-dimensional structure point cloud based on the positions of different structures in the unfolded depth map, wherein the structure types of each group of point clouds are the same. The technical problem of poor accuracy of structured data caused by manual measurement of thread steel data in the prior art is solved.

The invention relates to the technical field of railway signal safety control, and provides an interlocking product data analysis method, system and equipment, and the method comprises the steps: analyzing program language data in interlocking software, and obtaining a structural body type definition and a structural body variable; a multi-way tree is constructed according to the structural body type definition, and a multi-way tree model is optimized through node replacement; the optimized multi-way tree is adopted to carry out assignment analysis on the structural body variables, and structural body variable values are obtained; and verifying the obtained structural body variable value and input data, and outputting a verification result. According to the interlocking product data analysis method, system and equipment, structured analysis of interlocking program language data is realized by constructing the multi-way tree model and carrying out node replacement optimization, a complex data structure is efficiently processed, unanalyzed nodes are ensured to be correctly supplemented through a queue traversal and type replacement mechanism, and the data analysis efficiency is improved. And the integrity and accuracy of data analysis are improved.

The invention relates to a magnetic thrust assembly design method and device and a magnetic thrust prediction method. The method comprises the steps that the structure type and constraint conditions of the magnetic thrust assembly are obtained, and the structure type corresponds to at least one basic structure; constructing a structure parameter condition according to the structure type; and determining at least one group of target parameters of the magnetic thrust assembly based on an optimization algorithm and a thrust prediction model according to the structure parameter condition and the constraint condition. According to the method, automatic design of the magnetic thrust assembly is carried out through the optimization algorithm and the pre-trained thrust prediction model, so that the design time of the magnetic thrust assembly is shortened, and the design cost of the magnetic thrust assembly is further reduced.

A system may attempt to classify, according to field types, labels fields used by structures in instances of different log data source types, which use different structure types and different path information to access the structures of those structure types within the instances. Each of the structures includes at least one of the label fields and at least one data field associated with that label field. The system may store a result that includes the path information to access the structures and mappings of at least some of the field labels to the field types. The system may determine a field type involved in a system level query, and then generate a set of query graphs based on the field type and the result. The system may generate a set of instance level queries for a set of the instances according to the set of query graphs.

The invention provides a templated format conversion method and system for hierarchical metadata, and relates to the technical field of data format conversion, and the method comprises the following steps: receiving a metadata file in a JSON format; the method comprises the following steps of: recursively analyzing a metadata file in a JSON format, verifying fields of the metadata file in a manner of combining a structure tree model with a category label suspension mark, if the fields have an STRUCT structure body type, traversing all fields in an STRUCT structure body to generate a tree-shaped data structure, and if the fields have an ARRAY array type, traversing all fields in an ARRAY array to generate a tree-shaped data structure; if the field is of a basic field type, traversing the basic field to generate a set type data structure, and if the field is of a basic field type, traversing the basic field to generate a specific type data structure; the XML format file is generated according to different types of data structures, and the complete hierarchical relation of the original JSON format metadata file is reserved. The problems that in the prior art, unique complex types of metadata cannot be automatically processed, and nested structure output is not supported are solved.

The application discloses a kind of elastic modulus prediction calculation methods under the multiscale of ultra-high performance concrete, the prediction calculation method includes (1) according to material composition and representative volume element (RVE) size, the structure type of determining solution object;(2) according to the structure type of solution object, RVE unit internal component is divided into matrix phase and inclusion phase;(3) according to the volume content of matrix phase, elastic parameter and the morphology of inclusion phase, elastic parameter, volume content, the local strain concentration tensor of all inclusion phase is calculated;(4) according to the local strain concentration tensor of all inclusion phase, the elastic parameter of RVE is calculated using mean field theory.Compared with conventional test methods such as empirical formula method, finite element calculation method, this method is not only more suitable for a variety of doped ultra-high performance concrete composite materials, but also can improve the calculation efficiency of concrete elastic parameters under different scales.

The invention relates to the technical field of steel structure drawing, in particular to a modeling method and device for a frame structure and a storage medium. The method comprises the steps that a modeling environment is created, the modeling environment comprises a plurality of free datum lines, and the free datum lines are staggered to obtain a plurality of modeling nodes; in response to the modeling operation, a frame structure type selected by a user and a plurality of target modeling nodes are obtained, and the frame structure type comprises a first-class frame structure and a second-class frame structure; based on the modeling parameters of the first-class frame structure, generating the first-class frame structure at the plurality of target modeling nodes; and / or generating the second-class frame structure between the adjacent target modeling nodes based on the modeling parameters of the second-class frame structure. While the modeling speed of the frame structure is increased, the accuracy of the modeling position of the frame structure is considered, and the batch modeling efficiency of the frame structure is improved.

This application discloses a method and electronic device for rendering and displaying model output data, including: receiving and parsing current data from a structured document streamed by an artificial intelligence (AI) language model to predict the structure type corresponding to a target tag included in the current data; the structure type includes: a structure type defined for the main content in the structured document; if the markup language corresponding to the predicted structure type consists of multiple tags existing in pairs or groups, and the target tag belongs to a tag pair or group, then based on the other tags in the tag pair or group, temporary tags are added to the current data and provided to the rendering engine, so that the rendering engine can perform data rendering when it perceives the complete tags corresponding to the structure type in advance. Through this application embodiment, structural anomalies or structural mutations can be avoided or reduced.

The application discloses a preparation method of a high-plasticity hierarchical structure SnO2 reinforced modified silver-based composite material. The application quantitatively and stably prepares SnO2 reinforced phase powder with a sandwiched three-layer structure type and a hierarchical structure characteristic by using a crystal type transformation regulation and control new strategy, and combines a cumulative cold drawing process to prepare a new type of Ag / SnO2 composite material with high plasticity, solves the industry bottleneck problems of poor plasticity and high processing difficulty of a traditional Ag / SnO2 composite material, and promotes the industrialization process of the Ag / SnO2 composite material.

The invention relates to a construction structure safety monitoring method and system based on sensing data, and the method employs a domain learning mechanism, selects an engineering structure consistent with the construction structure in various construction specifications as a standard structure, and transmits the data distribution rule of the multi-source sensing data of the standard structure to the construction structure. Invariant features and basic structures among different structures which belong to the same structure type are mined; according to the method, two training branches are constructed, a first branch network extracts local features of multi-source sensing data through a CNN, a second branch network extracts global features of the multi-source sensing data through Transform, first graph feature vectors and second graph feature vectors are generated based on graph neural networks respectively, then the sensing data of the same category are aggregated and fused, and the multi-source sensing data is obtained. The fusion of local sensing features and global sensing features is realized, the training effect of the safety monitoring model is improved, and finally the prediction accuracy of the safety state of the construction structure based on the safety monitoring model is improved.

The embodiment of the invention provides a data processing method, device and equipment. The method comprises the following steps: generating to-be-written data; determining a structure type of the to-be-written data, wherein the structure type is a structured type or an unstructured type; under the condition that the structure type is an unstructured type, performing multi-modal feature analysis on the to-be-written data, and determining feature information of the to-be-written data; the feature information is used for indicating the content attribute, the security level and the use scene of the to-be-written data; and storing the to-be-written data in a target node according to the feature information, the target node being a computing node in a data cluster managed by the server. The data processing mode provided by the invention is suitable for read-write operation of the unstructured data.

The invention provides a binary organization automatic modeling method based on neper, and relates to the technical field of material science numerical simulation modeling, and the method comprises the steps: building a Thiessen polygon geometric model based on neper software, and obtaining a geo file corresponding to the geometric model; and on the basis of each crystal grain, the normal vector of the shared crystal face of each crystal grain and a plurality of adjacent crystal grains and the serial numbers of the crystal grains in the geo file, identifying the structure type of each crystal grain, so that the material parameters of the crystal grains are endowed according to the structure type of each crystal grain, and a double-state structure model is obtained. According to the method, the structure type of each crystal grain is automatically identified according to the serial number characteristic of each crystal grain in the geo file generated on the basis of the binary structure geometric model established by the neper software and the characteristic of the normal vector of the shared crystal face between the crystal grain and the adjacent crystal grain, so that the corresponding material parameter is given to each crystal grain; full-automatic modeling of the double-state organization is achieved, the modeling period is remarkably shortened, and the simulation efficiency is improved.

The invention relates to a method for producing a micro-optical representation arrangement which has a coloured motif layer (26), which is arranged in a motif plane and has a plurality of differently coloured micromotif elements (28-1, 28-2), and a focusing element grid (24) consisting of a plurality of microfocusing elements for viewing the micromotif elements (28-1, 28-2). In the method for producing the coloured motif layer (26), the following steps are carried out: - in an embossing step, an embossed structure with a multiplicity of structural elements (34, 36) is introduced into an embossing lacquer layer (32), which structural elements each correspond to one of at least two different structure types having different physical properties, - wherein the structural elements (34, 36) are all produced using the same embossing tool in a single embossing step such that the embossed structural elements (34, 36) are all in a defined phase relation determined by the embossing tool, and - in a processing step, the structural elements (34, 36) are selectively provided with at least one colouring material (40, 42) using the different physical properties of the respective associated structure type such that, when the representation arrangement is viewed, the structural elements (34) of a first structure type are visible in a first colour and the structural elements (36) of a second structure type are visible in a second, different colour.

The invention provides a structure prediction model suitable for alloy steel and an establishment method and application thereof, and the establishment method comprises the following steps: S1, obtaining component and structure type data of a plurality of steel grades covered by a component range, and calculating the statistical characteristics of each element by taking the mass fraction of the alloy element as a characteristic variable; s2, data processing is conducted, a decision boundary is obtained, and structure types are divided into single-phase austenite, austenite and ferrite or martensite, ferrite and / or martensite; and S3, predicting the model: performing dimensionality reduction on the obtained data by adopting the linear discriminant analysis in the step S2, combining softmax regression, performing linear discriminant analysis dimensionality reduction to obtain two LDA expressions, and obtaining a shaffler-like tissue prediction map according to the decision boundary straight lines of the corresponding three tissue types. Most material organizations can be correctly classified through the method, the accuracy is high, and the method is convenient to popularize and use in new materials and design components.

The present invention relates to the field of lattice structure design, and discloses a design method for an additive manufacturing lattice structure. The steps of drawing an envelope line and the following steps in the existing design are changed to drawing the Wv / Es-σ / Es diagram of each structure, and bringing the actual application parameters (energy absorption U and peak stress σ p ) into the diagram to directly obtain the structure type and the strut inclination angle. Then, the rod diameter d can be obtained through two simple equations, completing the design of the structure. This fundamentally avoids the repeated drawing of complex envelope diagrams and the use of complex equations when calculating the rod diameter d subsequently, making the entire lattice structure design process more convenient and having the potential for practical application.

The invention discloses a metamorphic rock area crystalline graphite ore prospecting method and system, and the method comprises the following steps: S1, constructing a structure-mineral-mineralization dynamic adaptation model: dividing the structure type of a target area, and building the corresponding relation of the structure type-ore body occurrence position; according to the method, the graphite flake diameter and the graphitization degree are analyzed, and a mineral characteristic-mineralization stage-resource potential correlation model is established. According to the prospecting method and system for the crystalline graphite ore in the metamorphic rock area, geoelectric data can be collected in all directions and a three-dimensional ore body prediction model can be generated through the arranged prospecting system in cooperation with constraint of a structure-mineral-mineralization dynamic adaptation model, the extension direction, the scale and the occurrence state of a deep ore body are clearly described, and the prospecting efficiency is improved. The detection limitation of a traditional two-dimensional technology is effectively broken through, the hidden ore body missed judgment risk is greatly reduced, and accurate target area guidance is provided for subsequent drilling.