12 results about "Data structure diagram" patented technology

Data structures, graphical user interfaces, and computer-implemented processes for automation of project management. In an embodiment, data structures are used to associate items with colors and elements. A virtual design board in a graphical user interface can then be automatically or semi-automatically populated with items that are associated with selected color(s) and / or element(s). A user may associate one or more of the populated items with a project, such as a wedding event. The underlying application may be cloud-based and / or be capable of managing clients and projects, processing payments, managing inventory, providing distinct libraries, creating assemblies, automatically generating preparation lists, generating reports, managing contracts, managing interactions, applying machine learning to make predictions or classifications and / or automate tasks, and / or the like.

To provide an image generation device, a trained model for image generation, a data structure for image generation, a program for image generation, and a diagnostic support method, for generating an image with reduced AN shadows from a biological image including the AN shadows.SOLUTION: A trained model for image generation is constructed by training a generative adversarial network, which is a type of a generative model, using original images X1-M created by pseudo-projecting virtual human body phantoms including a target tissue or organ O that contains AN and a target region T, and correct images X1-M. The trained model thus generates, from a biological image including AN shadows, an image containing only the AN shadows.SELECTED DRAWING: None

The invention discloses a static single assignment form query architecture which solves the problems that an existing SSA analysis tool is low in query efficiency and large in resource consumption in a large-scale code library. The framework comprises a front-end SSA intermediate presentation layer, an intermediate cache layer and a background database layer, wherein the front-end layer converts a source code into an SSA code comprising a node, a data flow edge and a control flow edge; the middle cache layer adopts a dynamic self-adaptive size to cache an intra-process data flow sub-graph, an inter-process data flow abstract and a hotspot query result; and the background layer stores the complete SSA data structure chart through an SQLite database. Millisecond-level response is realized through intelligent cache, I / O and memory overhead are balanced by combining lazy query and lazy storage strategies, and static analysis efficiency and resource utilization rate of a large-scale code library are remarkably improved.

The invention relates to the technical field of information transmission and data processing, in particular to an information flow intelligent compression transmission method based on big data, which comprises the following steps: acquiring key feature values of a multi-source heterogeneous data flow to generate a feature fluctuation mapping matrix, constructing a feature fusion data structure diagram, and generating a data flow priority main distribution diagram and a boundary distribution diagram block. And a priority level distribution surface is generated through feature value sorting and spatial reconstruction. According to the method, the compression strategy can be dynamically adjusted, the data transmission efficiency in a complex network environment is improved, the problems of limitation and information loss of a fixed strategy in a traditional method are effectively solved, and efficient and self-adaptive data flow priority analysis and transmission optimization are supported.

The invention relates to the technical field of electric power design assistance, and discloses an electric power design CAD drawing intelligent processing system based on an AI large model, and the system comprises an API gateway module which receives an examination request, and generates and distributes a request instruction; the task service scheduling module is used for receiving the request instruction and scheduling CAD analysis service, symbol recognition service, topology analysis service and rule engine service; the CAD analysis service analyzes the drawing file, recognizes graphic data and converts the graphic data into a digital model and a data structure; the symbol recognition service recognizes marking symbols in the graphic elements and the data structure and converts the marking symbols into business objects; the topology analysis service reads a business object, and establishes a spatial relationship and a connection logic; and the rule engine service verifies the digital model, the data structure, the graphic element, the annotation symbol, the business object, the spatial relationship and the connection logic, outputs a verification report, constructs an automatic drawing review system, and improves the efficiency and accuracy of electric power engineering design review.

The invention discloses a data extraction method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: acquiring a plant model, wherein the plant model is a three-dimensional model of a plant; according to the grid information of the plant model, structural data of a plant in the plant model is extracted, the structural data comprises hierarchical structure data and pivot point data, the hierarchical structure data represents hierarchies included in the plant model, and the pivot point data represents data related to joint positions of plant growth in the plant model; based on the structure data of the plant, a data structure chart corresponding to the plant model is generated, and the data structure chart is used for generating animation related to the plant. According to the method, the data extraction efficiency is improved.

This invention provides a bridge structure modeling method and apparatus based on graph data structures, belonging to the field of building information technology. The method includes: constructing a graph data structure for the bridge based on original engineering data; the graph data structure includes a set of nodes and a set of directed edges; the directed edges are associated with nodes in the node set that have dependencies and configured with rule functions; traversing along the dependency directions indicated by the directed edges, and using the rule functions to determine the component attribute data of component nodes and the rebar attribute data of rebar nodes; modeling the bridge to obtain a bridge structure model; and automatically updating the bridge structure model if the attribute data of the target nodes of the bridge structure model changes. This invention organizes nodes through a graph data structure and explicitly expresses mapping relationships and computational logic using directed edges configured with rule functions, thereby breaking the limitations of static parent-child relationships, effectively handling complex multi-directional dependencies between components and rebar, and achieving adaptive and linked updates when model parameters change.

A signature generator has been designed that can create a malicious campaign signature with substantial coverage of malicious campaign behavior without impeding benign traffic. The malicious campaign signature generator uses data of multiple, known malicious campaigns to identify abused, benign network entities. The signature generator builds a graph data structure for each malicious campaign that represents the abused network entities. The relationships encoded in the graph data structure indicate the use of the combination of abused network entities in the campaign. The signature generator aggregates the graph data structures and identifies a combination of the benign network entities that were highly abused across the multiple malicious campaigns with respect to all of the abused network entities represented in the graph data structures. A signature is then created from the identifiers of this combination of highly abused network entities.

A computer-implemented Influence Risk Engine harmonized with FIGS. 1-7, comprising data ingestion [100], volatility detection [110], exposure mapping [120], controversy analysis [130], and misalignment detection [140]. The system computes an Influence Risk Index (IRI) [500] and outputs mitigation recommendations [510] via dashboards [520] and APIs [530]. The architecture (FIG. 1), volatility / exposure analysis (FIG. 2), sentiment monitoring (FIG. 3), misalignment detection (FIG. 4), scoring (FIG. 5), data structures (FIG. 6), and machine learning pipeline (FIG. 7) are disclosed.

A signature generator has been designed that can create a malicious campaign signature with substantial coverage of malicious campaign behavior without impeding benign traffic. The malicious campaign signature generator uses data of multiple, known malicious campaigns to identify abused, benign network entities. The signature generator builds a graph data structure for each malicious campaign that represents the abused network entities. The relationships encoded in the graph data structure indicate the use of the combination of abused network entities in the campaign. The signature generator aggregates the graph data structures and identifies a combination of the benign network entities that were highly abused across the multiple malicious campaigns with respect to all of the abused network entities represented in the graph data structures. A signature is then created from the identifiers of this combination of highly abused network entities.

Embodiments of the present application disclose a data processing method and device, computer equipment and a readable storage medium. The data processing method comprises: determining a target object and a set of associated objects of the target object, and constructing a data structure graph between the target object and the associated objects; determining evaluation results corresponding to the target object and the associated objects respectively according to a reference evaluation matrix and a feature matrix of the data structure graph, wherein the reference evaluation matrix is determined according to reference evaluation parameters corresponding to the target object and the associated objects respectively; wherein the set of associated objects comprises a first type of associated object and a second type of associated object, the data structure graph comprises nodes for representing the target object and the associated objects, and comprises one or more of a first type of edge and a second type of edge, and the determination manner of the weight of the first type of edge and the weight of the second type of edge is different. The present application can effectively improve the detection coverage of the associated objects and the accuracy of the evaluation results.

The invention discloses an information collection method and device. Belongs to the technical field of communication. The method comprises the following steps: acquiring first information broadcasted by a telephone customer service system; a first node corresponding to second information broadcasted by the telephone customer service system last time is determined according to a first directed graph, and the first directed graph is a data structure graph used for storing interaction information with the telephone customer service system; on the basis of the first information, the first directed graph is updated, a second directed graph is obtained, the second directed graph comprises a second node corresponding to the first information and the connection relation between the first node and the second node, and the second node comprises a first response action set; determining a first response action meeting a target condition in the first response action set; and executing the first response action, and recursively executing the step of acquiring the first information broadcasted by the telephone customer service system until the communication connection with the telephone customer service system is interrupted.