592 results about "Usability" patented technology

The invention discloses a low-code platform based on a component library and a form engine, and relates to the field of data processing. The platform comprises a design system, an application system and a service system. The design system is provided with a form designer and a template manager, the form designer can configure a form component to generate a description file, and the template manager supports separate storage of a page template; the application system comprises a form analysis engine, a UI rendering engine and a reusable resource management component, the analysis engine analyzes configuration generation logic, the rendering engine loads a resource rendering page, and the reusable resource management component stores resources and generates configuration; the service system comprises a metadata analysis engine and an SQL assembler, the metadata analysis engine analyzes business rules to generate SQL and filtering strategies, and the SQL assembler generates operation statements adaptive to multiple data sources. Through the modular architecture design and the dynamic analysis mechanism, the problem that a low-code platform is insufficient in flexibility and usability is solved.

The invention discloses an industrial MBSE model generation and evaluation method based on a large language model, and the method comprises the steps: collecting and sorting an aerodynamic model, assembly design rules and related basic design parameters, and carrying out the formatted expression of the rules applied in MBSE, so as to form a special enhanced knowledge base in the industrial field; the method comprises the following steps: converting a demand described by a natural language of a user into a standard MBSE model code based on a large language model through a cue word engineering technology, selecting an optimization algorithm and a simulation algorithm through a function call technology, performing real-time optimization on the model according to a design target, and applying the generated MBSE model to propulsion device design and verification test. And determining availability and model consistency. Reconstruction and acceleration of digital design are realized through automatic configuration based on requirements and components. The method has remarkable advantages in the aspects of reliability, effectiveness and adaptability.

A data analytics system uses a grid-based data structure to improve the usability of LLMs in the analysis of large data sets, to synthesize information for use in other generative AI contexts, and to improve a user's ability to interface with an LLM. A grid-based data structure is a data structure or database that stores the results of column prompts applied to sources. The grid-based data structure may store the results in a relational manner. For example, a grid-based data structure may have rows that correspond to sources (e.g., documents, files, or databases) and columns that correspond to prompts. Each cell of the grid-based data structure stores the output of the column prompt applied to a source using an LLM. Thus, each column prompt may be systematically applied to each source to generate information based on the sources in an organized way.

The invention relates to the technical field of computer aided design, in particular to a text-driven CAD modeling method and system based on a diffusion and visual language model.The method comprises the steps that natural language text description is obtained, and CAD semantic features of the natural language text description are extracted; carrying out geometric standardization on the CAD semantic features by adopting a fine-tuning diffusion model, and generating a CAD view image conforming to engineering specifications; carrying out fusion by adopting a fine-tuned visual language model to generate a parameterized CAD construction sequence; a three-mode alignment mechanism is adopted, and the semantic consistency of the CAD semantic features, the CAD view images and the CAD construction sequences is checked; performing verification and post-processing on the CAD construction sequence, and outputting an executable Python code or STEP file; the CAD modeling method disclosed by the invention performs explicit modeling based on flexible modal description, and has the characteristics of high geometric constraint and high usability.

The invention discloses a memory enhanced script generation agent system based on RAG, and belongs to the technical field of artificial intelligence. The pre-learning and intensive training module takes a terminology library, an ambiguity explanation library and a script sample knowledge library as pre-learning blocks, adopts an intensive learning algorithm to train the generation module, and meanwhile, quantifies specific indexes to form a script scoring rule; the self-learning script generation module is used for realizing script generation; the long-term memory and knowledge tree management module is used for extracting, coding and storing key information layer by layer; the script evaluation and feedback closed-loop mechanism is used for grading and scoring the generated script through a preset quantitative evaluation index and feeding back the score to the self-learning script generation module; according to the RAG-based memory enhanced script generation agent system provided by the invention, flexible generation of a final high-quality script can be realized through cooperation of multiple agents, the sense of makeup is reduced, and the usability and usability are improved.

The invention belongs to the technical field of big language model security, and particularly discloses a defense method and system for big language model cue word attack, a terminal and a medium. Comprising the steps of receiving information content input by a user, and generating a plurality of detection input copies based on a preset rule; inputting the copies into mutually independent detection processes in parallel to obtain a plurality of risk scores; constructing a comprehensive risk score based on the risk score, and determining a risk level of the input content according to the comprehensive risk score; when the risk level falls into a defense triggering interval, executing an active defense strategy, and implementing instruction confusion, semantic dilution and structural isolation processing to generate first output content; when the risk level is below a pass threshold, second output content is generated based on the user original input. According to the method, on the premise that normal interaction experience is not affected, fine-grained, controllable and dynamic safety protection can be carried out on multi-type cue word attacks, and the overall safety and usability of a large language model are improved.

The invention discloses a fault diagnosis method and system for a coil cutting all-in-one machine based on a large language model, and relates to the technical field of equipment fault diagnosis, and the system comprises a table data intelligent processing module, a knowledge base construction module, a diagnosis reasoning module and a user interaction module. The table data intelligent processing module is used for carrying out automatic fault mode labeling and description standardization on a cutting and rolling all-in-one machine fault diagnosis case library provided by a user; the domain knowledge graph construction module is used for integrating the standardized table database and automatically constructing a domain knowledge graph; the diagnosis reasoning module is used for performing fault diagnosis reasoning based on a large language model and a knowledge graph; and the user interaction module provides a multi-modal user interaction interface and supports visual display of fault diagnosis. Therefore, by adopting the fault diagnosis method and system for the cutting and winding all-in-one machine based on the large language model, the intelligent level of fault diagnosis can be improved, the knowledge base construction and expansion cost can be reduced, and the usability and maintainability of the system can be enhanced.

The invention discloses a natural language driven mechanical arm control method, device and equipment, a medium and a product, and relates to the technical field of artificial intelligence and robot crossing. The method comprises the steps that after a natural language instruction and multi-mode perception data are obtained, the natural language instruction is decomposed into semantic embedding vectors, large language model hierarchical semantic analysis is adopted to obtain structured task representation, and then the multi-mode perception data are fused to generate environment representation needed by task execution. And then the structured task representation and the environment representation are converted into a task graph, the task graph is converted into a joint control instruction of the target mechanical arm, and finally the joint control instruction is sent to a joint controller to be executed, so that through multi-level semantic understanding, multi-mode perception fusion and self-adaptive execution control, the joint control accuracy is improved. Accurate understanding and efficient execution of the mechanical arm on complex natural language instructions can be achieved, and the task execution precision, adaptability, flexibility, usability and intelligent level of the mechanical arm in a dynamic environment are improved.

The invention discloses a three-dimensional model intelligent generation method and system based on a natural language, and the method comprises the steps: receiving and describing the natural language inputted by a user in real time, based on the three-dimensional model data structure, the de-noising symbol set and the stop word list, key information data are extracted according to natural language description and mapped into a three-dimensional model parameter set; according to the scene type described by the natural language and the three-dimensional model parameter set, calling a three-dimensional model generation network corresponding to the scene type described by the natural language to generate an initial three-dimensional model; and receiving and analyzing a model optimization instruction input by a user in real time, updating the geometric structure, detail features and physical attributes of the initial three-dimensional model according to an analysis result, generating a dynamic interaction model, and outputting a three-dimensional model file of the dynamic interaction model. By applying the method and the system provided by the invention, the efficiency, the accuracy, the flexibility, the usability and the user experience of three-dimensional model modeling are improved.

The invention discloses a software and hardware combined data interaction method and system based on a Modbus communication component. According to the method and the system, different types of Modbus slave devices are managed through a unified communication configuration file and a point table configuration file, so that compatible access to heterogeneous devices is realized; through an optimized point table analysis mechanism, efficient and self-adaptive data acquisition of discontinuous register addresses is supported, and fine processing and conversion are performed on different data types; a graphical configuration management tool is provided, and the equipment configuration and point table management process is simplified; and a standardized command model is used, so that unified control and data interaction of an upper-layer application on Modbus equipment are facilitated. According to the invention, the flexibility, usability and data interaction efficiency of Modbus communication can be remarkably improved, the system integration and operation and maintenance cost is reduced, and an efficient and reliable Modbus communication solution is provided for the field of industrial automation.

The embodiment of the invention discloses a terminal application behavior data analysis method and computer equipment, and the method comprises the steps: obtaining an interaction behavior data set of an RPA terminal application in a preset time window, the interaction behavior data set comprising a plurality of interaction behavior sequences, each interactive behavior sequence comprises at least one user interface operation event and a corresponding system response event; performing behavior track analysis processing on the interactive behavior data set, and extracting an interface circulation feature and an operation intention feature of each interactive behavior sequence; generating an interface optimization strategy according to the relevance between the interface circulation feature and the operation intention feature, wherein the interface optimization strategy comprises an interface layout adjustment rule and an interface response logic optimization rule; and feeding back the interface optimization strategy to a background management system of the RPA terminal application. Therefore, the problem that an existing RPA application interaction interface is insufficient in design and optimization can be effectively solved, and the usability of the interface and the response capability of the system are improved.

The invention discloses a retrieval enhancement generation method and system based on large model multi-level sorting, and the method comprises the steps: carrying out the multi-round rewriting and disassembly operation of a question inputted by a user, and carrying out the analysis and summarization of the disassembled data, so as to obtain the disassembled data; performing intention analysis by utilizing an intention recognition optimization model on the basis of the disassembly data, and obtaining weight data corresponding to each intention; based on the weight data corresponding to each intention and the constructed knowledge base, performing multi-source recall by using a retrieval enhancement generation technology to obtain a multi-source recall result; and performing multi-level sorting on the multi-source recall result to obtain a retrieval result. According to the method, the user intention recognition model, the satisfaction sorting based on the thinking chain technology and the availability sorting based on the large language model are introduced, so that the real requirements of the user are accurately understood, the accuracy and quality of the generated content are improved, the complex and professional problems are solved, and the actual application requirements are met.

A data analytics system uses a grid-based data structure to improve the usability of LLMs in the analysis of large data sets, to synthesize information for use in other generative AI contexts, and to improve a user's ability to interface with an LLM. A grid-based data structure is a data structure or database that stores the results of column prompts applied to sources. The grid-based data structure may store the results in a relational manner. For example, a grid-based data structure may have rows that correspond to sources (e.g., documents, files, or databases) and columns that correspond to prompts. Each cell of the grid-based data structure stores the output of the column prompt applied to a source using an LLM. Thus, each column prompt may be systematically applied to each source to generate information based on the sources in an organized way.

The present invention relates to the field of network technology and security, and in particular, to a scenario-based self-learning method and system for detecting malicious requests. The method mainly comprises: scenario-based one-click configuration, customized configuration of detection granularity and strategies, and an integrated scoring engine that combines anomaly scores obtained from different detection strategies. In addition, the method also comprises generating configuration feedback suggestions on the basis of traffic self-learning and presenting same to a client in a clear and operable manner. The client can adjust configurations on the basis of the feedback suggestions, generate personalized scenario plans for seamless application, and conduct gray box testing before deployment to ensure the usability of the current scenario-based configuration. The present invention achieves the configuration of flexible and adaptive capabilities for service scenarios by finely categorizing requests for different scenarios, applying different traffic restrictions for different scenarios, and combining different detection functions for different scenarios, so that the security detection capability of scenarios is improved, and missed detections and false positives caused by general configurations are reduced.

The invention relates to the technical field of monitoring and data acquisition systems, and discloses an SCADA (supervisory control and data acquisition) system based on a large language model, an implementation method and equipment, and the system comprises a user interaction terminal which receives a natural language instruction input by a user and displays a dynamic user interface; the natural language processing module is used for preliminarily analyzing the natural language instruction to obtain a user intention and key information; the large language model is used for deeply analyzing the user intention and the key information and generating a task description or a task execution plan; the MCP arrangement engine is used for mapping the task description or the task execution plan to a predefined function to obtain executable structured data; and the dynamic UI generator is used for generating a dynamic user interface based on the executable structured data and a preset UI instruction. According to the method, the usability and the data analysis capability of the SCADA system are improved through natural language interaction, and meanwhile, the reliability and the safety of the system are ensured by utilizing an MCP and a predefined function mechanism.

The invention relates to the technical field of data processing, and particularly provides a script generation and model training method and device, a storage medium and a program product. In the invention, the definition protocol is extracted based on the real script data and is used for describing the script characteristics and requirements of the corresponding script type, so that the prompt information is constructed based on the definition protocol and the script generation request initiated by the user in the script generation scene; therefore, the generation direction and range of the script generation model are guided and indicated based on the prompt information, so that the script content generated by the script generation model is more flexible, the script characteristics and requirements required by each script type are better met, the actual script application requirements are met, and the usability is relatively high. In conclusion, the technical scheme provided by the invention can solve the problems of simple and mechanical script generation mode and poor practicability in related technologies to a certain extent.

The invention belongs to the technical field of informatization management, and particularly relates to a data import method based on similarity calculation, automatic matching of file fields and database fields is realized by calculating the similarity of the file fields and the fields in a database, and the workload of manual configuration can be effectively reduced; a common editing distance calculation similarity algorithm is improved, the influence of the longest common subsequence on similarity calculation is considered, a similarity calculation formula is improved, and the matching success rate is increased; when the similarity is calculated, literal matching and semantic matching can be carried out by adopting a method of combining an improved editing distance similarity calculation algorithm and word semantic similarity calculation based on the Zhinetting, so that the matching success rate is effectively improved; besides automatic matching, a user configuration interface is provided, a user can manually adjust the mapping relation, and the flexibility and usability of the method are improved; user configuration content can be automatically recorded, and repeated configuration work of a user is avoided.

The invention provides a vulnerability scanning method, electronic equipment, a readable storage medium and a computer program product. The method comprises the following steps: receiving a natural language instruction input by a user; recognizing the natural language instruction through an intention recognition model to obtain an instance statement recognition result; determining a system call statement corresponding to the instance statement recognition result according to a vector database; triggering a vulnerability scanning management system to execute a corresponding scanning task according to the system call statement to obtain a scanning result; performing vulnerability risk analysis according to the scanning result to obtain a vulnerability analysis result; generating a scanning report according to the scanning result and the vulnerability analysis result; and outputting the scanning report on the interactive interface. Therefore, according to the method, efficient and flexible operation of vulnerability scanning management can be achieved according to the natural language instruction input by the user, a tedious customized development process does not need to be carried out, the universality and usability of the system are improved, and the operation and maintenance cost of the system is reduced.

This application provides a data sharing method, including: A first data management system receives a first query statement; obtains, based on the first query statement, a second query statement by using a software development kit of a second data management system; and then accesses a unified open access service of the second data management system based on the second query statement, to obtain proprietary-format data in the second data management system. In the method, a data management system may provide a software development kit SDK to the outside, such that another data management system such as a big data engine can access a unified open access service by invoking the SDK, so as to support sharing of proprietary-format data with the outside, breaking a limitation that proprietary-format data is shared only within a system, and improving usability.

Provided is a technique in which, in arranging a virtual object with respect to a real space, a user has less trouble, usability is good, and the object is suitably placeable. A head mounted display apparatus (HMD apparatus) according to one embodiment has a function of arranging and displaying the virtual object in a space based on an operation by a user. The HMD apparatus displays, on a display surface, a grid including a plurality of points for supporting an operation of the virtual object, and disposes and displays, according to an operation includes designation of a target virtual object and designation of a first point at an arrangement destination, the target virtual object at the position of the first point.

The invention provides an automatic bug fixing method based on a large model sensing dynamic program state. The method comprises the following steps of: 1, running verification: verifying existence of vulnerabilities through running, and extracting non-crash constraints; step 2, obtaining an expected state in a repair positioning step, obtaining the expected state based on non-collapse constraint, specifically obtaining the expected state of a collapse position and obtaining the expected state of a potential repair position; 3, a debugging process in the positioning step is repaired, an interface set is provided for the LLM, a program real state is obtained based on program debugging, and static information is obtained based on a tool set; and 4, summarizing debugging information, and generating and verifying patches. According to the method, an actual running state is obtained through program debugging, and an expected state is deduced based on collapse free constraints. By continuously comparing the two states, the nature of the vulnerability can be deeply understood, so that a more accurate and effective repair patch is generated, and the patch repair accuracy, effectiveness and actual availability are remarkably improved.

A five-axis numerical control glue dispenser control method based on track adjustment comprises the steps that a UG model generates a G code through a rear processor, and a feature adjustment point of a track is marked in the G code; loading and generating a debugging point list according to the G code, acquiring debugging information of a debugging list, and generating debugging data according to a preset rule; judging whether the debugging point information is modified or not, if the debugging point information is not modified, running the debugged G code, judging whether the debugging point information is modified or not when the G code runs again, and controlling the five-axis numerical control dispenser to run by running the debugged G code. The graphical easy-to-use operation interface is used for completing numerical control program generation, the special glue dispensing track and speed adjusting function, the special glue dispensing amount and switch control function and the like are achieved, and the technical requirements of glue dispensing are met. The overall matching method can effectively solve the technical problems which cannot be solved through a traditional control method.

The invention provides a humanoid robot data set quality evaluation method and a humanoid robot data set quality evaluation system based on multi-dimensional evaluation, and provides a systematized and standardized evaluation process aiming at the quality problems of the existing robot multi-modal data set in the aspects of normalization, integrity, accuracy, consistency, timeliness, accessibility, availability and the like. According to the method, an automatic tool is combined with manual auditing, the structure, metadata, annotation content, data formats, multi-modal alignment and the like of a data set are comprehensively detected, a deep learning algorithm is introduced to achieve detection of pornographic pictures and sensitive words of visual content, and content safety and compliance are effectively improved. The system can flexibly adjust the weight of each evaluation dimension according to different application scenes, automatically generates a quality evaluation report, and supports continuous monitoring and optimization and improvement. Practical application shows that the method can significantly improve the overall quality of the robot data set, and provides reliable data basis and technical support for intelligent training and application of the robot.

A data analytics system uses a grid-based data structure to improve the usability of LLMs in the analysis of large data sets, to synthesize information for use in other generative AI contexts, and to improve a user's ability to interface with an LLM. A grid-based data structure is a data structure or database that stores the results of column prompts applied to sources. The grid-based data structure may store the results in a relational manner. For example, a grid-based data structure may have rows that correspond to sources (e.g., documents, files, or databases) and columns that correspond to prompts. Each cell of the grid-based data structure stores the output of the column prompt applied to a source using an LLM. Thus, each column prompt may be systematically applied to each source to generate information based on the sources in an organized way.

The invention discloses a lightweight differential privacy federal learning method for cross-domain management and control of power data. The method comprises the following steps: S1, performing initialization setting; s2, performing local training and parameter processing on the client; s3, uploading and aggregating parameters; s4, privacy loss evaluation and parameter adjustment; s5, pruning and compressing the model; s6, privacy protection and full mask multiplexing based on secret sharing; and S7, preventing collusion attacks. According to the method, the calculation complexity is remarkably reduced, and the core contradiction that privacy protection and model practicability are difficult to consider in cross-domain cooperation of power data is solved; the problems of high communication overhead and insufficient computing power of edge equipment during massive power data processing of traditional federated learning are solved, and the real-time performance and expandability of cross-domain cooperation are remarkably improved; while data availability is guaranteed, complex threats such as multi-client collusion and man-in-the-middle attack are effectively handled, and a privacy protection framework with a higher security level is provided for multi-agent cooperation of a power system.

The invention discloses a zero-code heterogeneous data integration method. The method comprises the following steps: S1, configuring a multi-source data connector; s2, processing differences of different data formats and structures by adopting an adapter mode; s3, performing data cleaning; s4, performing data conversion; s5, loading the converted data into a target database or a data warehouse, and adopting a partition loading and incremental updating strategy; s6, providing a graphical user interface, and constructing a data integration workflow by dragging the component and connecting the data flow; s7, providing a visual workflow management tool, and supporting workflow version control, collaborative editing and parallel processing; s8, realizing an automatic workflow scheduling system, and supporting timed tasks and event driving; s9, performing data consistency check and integrity verification; and S10, a modular and extensible system architecture design is adopted. A zero code integration method is adopted, efficient integration of heterogeneous data sources is achieved, and the method has the advantages of being high in usability, high in processing efficiency and capable of guaranteeing data quality.

The invention provides a robot task planning method and device, computer equipment and a storage medium, and the method comprises the steps: receiving a natural language instruction of a user; determining a task target based on the natural language instruction and scene context information; constructing a semantic map based on the environment data and the visual identification and relation reasoning result; based on the task target and the semantic map, generating an action sequence through a formalized planning engine; and controlling the robot to execute the action sequence. By adopting the method, the usability, accuracy and reliability of robot task planning can be improved.

The present disclosure provides a northbound application programming interface (API) invoking method and apparatus. The method comprises: receiving an authorization request message that is sent by a common API framework (CAPIF) verification and authorization function and that requests acquisition of a specified authorization (101), the specified authorization being an authorization corresponding to a target resource of UE; on the basis of the authorization request message, determining whether to allow an API invoker to acquire the target resource (102); and sending an authorization response message to the CAPIF verification and authorization function (103), the authorization response message being used to indicate whether the UE agrees to provide the specified authorization for the API invoker. According to the present disclosure, the API invoker can acquire a target resource of a target resource owner on the basis of a user authorization, achieving the purpose of enabling the user authorization in the API invoking process, and usability is high.

The invention relates to the technical field of diffusion model AI application, and discloses an AI aided design workflow method and system based on a diffusion model, and the method comprises the steps: receiving multi-modal data; vectorizing the sketch, and extracting key set features; analyzing the text into structured semantics; parameter constraints are converted into mathematical expressions or boundary conditions; mapping the multi-modal data to a unified space; selecting a generation path with the minimum loss function from the candidate paths; gaussian noise is gradually added into the submerged space, and noise distribution is predicted; injecting the parameter constraint into a denoising process to generate a path; and the optimized latent vector is converted into a vector graph through a decoder, and a geometric topological relation is reserved. The system comprises a unified multi-modal data module, a path generation module and a user interaction module. According to the method, the actual availability of a design result is improved; the design period is shortened, the process is simplified, and human resource investment is reduced.

The invention relates to the technical field of building maintenance scheme optimization, and discloses a building maintenance scheme optimization method based on an intelligent algorithm, and the method specifically comprises the following steps: 1, interface optimization: after starting MATLAB software, loading a source code of building quality diagnosis system software named as a building doctor, and in a design view interface of the software, carrying out interface optimization on the source code of the building quality diagnosis system software; according to the method, the user interface of the software is ensured to be clearly viewed, then a'optimization 'button in the interface is optimized and adjusted, a'help' menu is newly added in the software interface, and visual elements such as the graphic size and color matching of the user interface are finely optimized and adjusted, so that the functionality of the software is enriched, and the user interface is more vivid. In addition, the friendliness and usability of the user interface are remarkably improved, smoother and more comfortable use experience is brought to the user, the visual and clear user interface is elaborately designed, and it is ensured that the user can easily understand and operate the platform and detect the particularity of the building.