12 results about "International standard" patented technology

The invention discloses an international standard transformation evaluation method based on cross-granularity feature cross fusion, and relates to the technical field of natural language processing, and the method comprises the steps: 1, collecting a standard class international standard text, and constructing an international standard transformation evaluation index system; 2, constructing an international standard conversion evaluation data set according to the standard international standard text; 3, constructing a cross-granularity feature cross fusion index classification model according to the CNN network, the BERT network and the bidirectional long short-term memory network; 4, training a cross-granularity feature cross fusion index classification model by using an international standard conversion evaluation data set; step 5, constructing an index score assignment rule; and 6, inputting a to-be-evaluated international standard text into the trained cross-granularity feature cross fusion index classification model to obtain a text prediction classification, and calculating an evaluation result in combination with an index assignment rule. According to the method, the international standard conversion evaluation efficiency, rationality and accuracy are effectively improved by using the deep learning algorithm.

The invention discloses a national standard bid acquisition evaluation method based on multilayer cross recombination attention, and belongs to the technical field of national standard bid acquisition evaluation, and the method comprises the steps: extracting the text content in a to-be-evaluated international standard file, and splitting the text content into a plurality of parts of text data; inputting each piece of extracted text data into a multi-layer cross recombination attention index classification model to obtain a prediction indication feature corresponding to the text data; the multi-layer cross recombination attention index classification model comprises a data coding and feature mapping module, a deep cross attention module, a multi-scale fusion cross attention module, an attention cross recombination module and an index indication module; and performing score calculation on the international standardized file according to the prediction indication characteristics corresponding to all text data in the same international standardized file to obtain an evaluation result in the to-be-evaluated international standardized file. According to the invention, the matching degree between the international standard and the domestic standard can be automatically and accurately evaluated by using the deep learning algorithm.

The invention relates to the field of load balancing, and particularly discloses a national standard signaling load balancing system and a national standard signaling load balancing method based on elb and redis, which are characterized in that registration and session state data of all equipment are stripped from a signaling server and are converted into a high-availability shared cache for centralized persistence, so that the signaling server becomes a stateless computing node. When the load balancer detects that any signaling server fails, the load balancer accurately and smoothly redirects the subsequent signaling of the affected device to another healthy takeover server in the cluster by using the orderliness of the consistent Hash algorithm. As all the servers maintain the complete mirror image of the global device state in the local memory in advance, the takeover server can immediately identify the device and seamlessly recover the session. In this way, the problems of session loss and large-scale re-registration storm caused by server faults are solved.

The invention is applicable to the technical field of computer aided design, and provides an automatic tolerance labeling method based on a multi-modal large model, which comprises the following operation steps: receiving an STP file of an assembly as input, analyzing the structure of the assembly, calculating geometric information of parts and feature surfaces, distributing a unique identifier and establishing an assembly tree; and through shell part identification and a centroid-based iterative RANSAC profile extraction algorithm, generating a multi-view overall image and a profile image. According to the automatic tolerance labeling method based on the multi-modal large model, the manual labeling time is greatly shortened by automatically extracting geometric information and generating part description and tolerance labeling, and through guidance of a rule base and an international standard, it is guaranteed that tolerance labeling is standard and unified, the risk of human errors is reduced, and the accuracy of the manual labeling is improved. The multi-modal large model is combined with geometric data and natural language description, comprehensive understanding of part functions and assembly relations is achieved, the reasonability of tolerance marking is improved, and the method is suitable for multiple parts.

The embodiments of the present disclosure disclose a method, device, equipment and storage medium for constructing barrier-free components. The method includes: in the current web page, detecting whether a business component is set at a target location with barrier-free access requirements; in response to a business component being set at the target location, obtaining a constructed basic component corresponding to the barrier-free access requirements; determining configuration information according to the basic component and the business component; when the basic component packages the business component, configuring the above configuration information in the business component to construct the barrier-free component. In the technical solution of the embodiments of the present disclosure, during the development process, since the basic component already complies with the international standards related to barrier-free access, there is no need to consider the international standards in the process of constructing barrier-free components based on the basic component; since the barrier-free component is constructed on the basis of the business component, barrier-free access and business logic can be decoupled, simplifying the difficulty of barrier-free access development.

The present invention provides a high-compatibility microphone, which relates to the technical field of microphones. The high-compatibility microphone comprises a microphone head (3); and a four-stage headphone plug (1) for outputting an audio signal picked up by the microphone head (3); the microphone further comprises a mode switching device (2), the mode switching device being connected between the microphone head and the four-stage headphone plug, and being used to switch the connection position of the microphone head (3) and the ground at the four-stage headphone plug (1), so that the signal output position of the four-stage headphone plug (1) is compatible with a three-stage headphone socket, a four-stage national standard headphone socket or a four-stage international standard headphone socket. The microphone has the characteristics of good compatibility, simple circuit, compact structure, and easy miniaturization.

A system is provided for implementing an international standard-based resource transmission request rerouting tool. The system may perform operations that comprise: receiving a first set of resource transmission requests that are associated with the resource transmission network; redirecting, away from a legacy processing platform of the resource transmission network, the first set of resource transmission requests to a resource transmission request routing engine; performing, by the resource transmission request routing engine, a preliminary analysis by evaluating each resource transmission request against at least one from among a first set of rules and a first set of filters; based on the preliminary analysis, forwarding, by the resource transmission request routing engine, the resource transmission request to an corresponding processing platform; and processing, by the corresponding processing platform, the resource transmission request.

The invention discloses an ISOS-CFAR (International Standard Organization Standard-Call False Alarm Rate) detection method based on The method comprises the steps that a to-be-detected unit set is acquired, and the to-be-detected unit set comprises a plurality of to-be-detected units; performing SO-CFAR detection on each to-be-detected unit in the to-be-detected unit set, and outputting a first detection result; when the first detection result is HOS1, setting the detection mark corresponding to the unit to be detected as 1, and when the first detection result is HOS0, setting the detection mark corresponding to the unit to be detected as 0; and performing OS-CFAR detection on all the to-be-detected units with the detection marks set to be 1, and outputting a second detection result. According to the method, the technical problems of large calculation amount and long time in the detection process of the existing mean value class constant false alarm detection and ordered statistical class constant false alarm detection methods are solved.

A blockchain-based system and method for verifying Certificates of Authentication (COAs) in supply chain management is disclosed, adhering to ASTM D8558-24 guidelines and relevant ISO standards including ISO / IEC 27001, ISO 28000, and ISO 9001. The system utilizes a custom Layer 1 (L1) blockchain built on the Avalanche platform, implementing a dual-token model to create, manage, and verify COAs as Non-Fungible Tokens (NFTs). It features AI-powered authentication, enhanced security measures, and a data marketplace for monetizing authenticated supply chain data. The system offers improved scalability, customization for various industries, and facilitates both B2B and B2C transactions. With cross-chain communication capabilities and integration with existing supply chain systems, the invention addresses environmental and social considerations while providing comprehensive interoperability. This solution aims to revolutionize supply chain authentication, offering enhanced transparency, efficiency, and trust in global trade, all while maintaining compliance with international standards for security, quality, and supply chain management.

The invention relates to the technical field of medical information, in particular to an international-oriented traditional Chinese medicine operation standardized coding and multi-language mutual recognition method, which comprises the following steps of: constructing a multi-language parallel corpus; extracting traditional Chinese medicine nursing operation terms, generating hierarchical standardized codes, and associating multi-language translation names to form a term library; establishing a mapping relationship between the code and an international general medical term library; generating a standardized data packet through a multi-center mutual recognition service based on the mapping relationship; and carrying out block chain evidence storage on the key operation. According to the method, the problem that cross-border mutual recognition of traditional Chinese medicine nursing operation is difficult due to non-standard terms, lack of multi-language support and disjunction from international standards is solved, accurate understanding, efficient mutual recognition and credible tracing of traditional Chinese medicine nursing service in a cross-border scene are achieved, and internationalized popularization of traditional Chinese medicine service is powerfully supported.

The invention discloses an intelligent document coding system and method based on rule driving, and belongs to the technical field of intelligent document processing. According to the system, a three-level DCC coding rule tree (A1 technical field-> A2 main class-> A3 subclass) fusing international standards, national standards and enterprise self-defined requirements is constructed; a two-stage analysis mechanism is adopted, wherein file name information is extracted in a structured mode, and RAG enhanced content analysis is started when the confidence coefficient is lower than 0.8; generating an initial code through the Qwen-72B large model in combination with the structured Prompt, executing format verification, and outputting a compliant code; constructing a hierarchical classification tree based on a coding result and performing multi-dimensional statistics; meanwhile, the matching degree of a file name and a code is calculated, a case lower than 0.6 is marked as a nonstandard case, and a naming template is dynamically generated by utilizing a high-matching case, so that closed-loop iterative optimization of naming specifications is realized. According to the method, coding standardization, automation and traceability are improved.

This invention discloses a cross-system interconnection and compliance detection system for general governance rules of artificial intelligence, belonging to the field of artificial intelligence security governance technology. The system includes a hardware-isolated security main control module, a cross-system standard interconnection protocol stack, a non-intrusive behavior acquisition module, a multi-domain governance rule matching engine, a compliance closed-loop verification module, and a result anti-tampering evidence storage module. This invention adopts a hardware isolation architecture to build an isolated operating environment, realizes the interconnection of heterogeneous AI systems without modification based on an international standard protocol stack, collects operating data through non-intrusive technology, completes dynamic verification by combining hierarchical compliance baselines, controls violations through hardware isolation layer instructions, and completes full-link data evidence storage and traceability based on encryption technology. This invention solves the technical problems of existing technologies, such as strong invasiveness, poor compatibility, easy tampering of compliance control, and lack of international standard adaptation, and can be applied to the compliance governance of various types of artificial intelligence systems.