15 results about "Verification and validation" patented technology

The invention provides a standard document automatic generation and multi-dimensional auditing method and system based on a large model, and relates to the technical field of artificial intelligence, and the method comprises the steps: 1, building a distributed database of a multi-source document, and analyzing a heterogeneous text through natural language processing to obtain a standardized knowledge network; step 2, extracting index elements based on the standardized knowledge network, and forming a structured parameter library through verification and verification; and step 3, based on the structured parameter library, constructing a template library, analyzing user demands in combination with semantic matching, and automatically generating a standard document outline. The document generation efficiency and quality are improved, the manual auditing cost is reduced, and the auditing comprehensiveness and accuracy are enhanced.

Systems, methods, and computer-readable storage media for verification and validation of cyber resilience in a distributed entity or third-party network (DETPN). One system includes one or more processing circuits including memory and at least one processor configured to access or identify compliance data for at least one of a plurality of entities or third-parties, the compliance data corresponding with a first timing phase. The at least one processor further configured to access or identify at a second timing phase updated compliance data for at least one of the plurality of entities or third-parties based at least on environmental data of the DETPN. The at least one processor further configured to generate one or more tokens comprising at least one of the compliance data or the updated compliance data. The at least one processor further configured to provide the one or more tokens.

Systems and methods provide a HybridOps model for the identification, capture, isolation, feature engineering and adjudication of source signal data signatures for inclusion in calibration quality standard reference signal data signature libraries that improve machine learning and validation, reduces model bias and reduces model drift. The HybridOps model may include an “unlocked” AI / ML (machine learning enabled) public facing deployment pipeline in parallel with a clone AI / ML deployed in an internal development environment using a ML-Ops pipeline and in parallel with a clone“locked” AI / ML (machine learning disabled) as a standard reference. The three deployed models enables monitoring and measuring model drift, context drift and product progression for improved verification and validation of model reliability. The parallel environment AI / ML testing using randomized learning, validation, testing sets drawn from calibration quality adjudicated standard reference signal data signature libraries provides for validation, verification and test to failure procedures.

A distributed resource group scheduling and group control system relates to the technical field of information transmission, and comprises a data acquisition module used for collecting operation parameters of distributed energy resources, including but not limited to generation power, voltage, current and temperature; the compression and encryption module is used for compressing and encrypting the collected data; the transmission network is used for transmitting the compressed and encrypted data and supporting efficient and safe data transmission; the receiving end decoding module is used for decrypting and decompressing the received data, recovering the original information, and checking and verifying to ensure the integrity and authenticity of the data; the compression and encryption module comprises an adaptive prediction model compression algorithm and a hybrid encryption mechanism; the group control decision module is used for performing group control on the distributed resources based on the received data; through a data compression algorithm, the transmission data volume is greatly reduced, so that the transmission speed is improved.

The invention discloses a machine room resource capacity intelligent planning system and method based on multi-source data fusion, and belongs to the technical field of data center management, and the system comprises a multi-source data collection module, a resource manifold modeling module, a geodesic optimization module, a self-adaptive planning module and a verification and inspection module. The method comprises the following steps: mapping multi-dimensional resource parameters such as space, power, heat dissipation and load bearing of a machine room into a Riemannian manifold mathematical model, and constructing a resource measurement tensor representing a resource distribution density and a constraint relationship; calculating a resource allocation optimal path on the resource manifold, constructing a multi-objective function including space utilization rate, energy efficiency, heat dissipation efficiency and cost effectiveness, and generating an optimal deployment scheme of the machine room equipment; in combination with topological characteristic analysis of resource manifolds, potential resource bottlenecks are predicted, and a resource allocation scheme is dynamically adjusted; and the security and compliance of the evaluation scheme are verified through digital twinborn simulation, so that the problem of unbalanced resource allocation caused by independent planning of each system in traditional machine room planning is solved.

The deployment of large language model (LLM) and retrieval-augmented generation (RAG) systems in industrial automation environments present unique technical challenges that are not adequately addressed by conventional software validation approaches. A computing system can define a comprehensive architecture with cross-validation methodologies that can perform systematic detection of complex failure modes that might be missed by conventional testing approaches, while providing the reliability, safety, and real-time performance characteristics essential for successful deployment of LLM and RAG systems in industrial automation environments.

In an integrated circuit (IC) analysis, a reference IC layout is stored. Instructions are readable and executable by an electronic processor to perform an IC analysis method, including: receiving layer images of a physical IC; extracting polygons depicted in the layer images; detecting errors in the physical IC by applying homeomorphic error detection to compare the extracted polygons with polygons of the reference IC layout; and displaying the detected errors on the display. The detecting of errors may include detecting an error comprising a topological inequivalence between an extracted polygon or pair of polygons and a polygon or pair of polygons of the reference IC layout. The detecting of errors may include detecting an error comprising a topological coverage error.

The application discloses a kind of CFD verification and confirmation mark mould data storage method and database, belong to aerodynamic database technical field, including steps: CFD verification and confirmation mark mould data warehousing;Extract mark mould example basic information again, parse, organize example test / calculating result structure data, design form CFD verification and confirmation mark mould data table;The CFD verification and confirmation mark mould data table includes core data table.The application can realize the dynamic storage of different standard examples of incoming flow state data and result data, reduce data redundancy, improve data scalability, can ensure that database platform can accurately, efficiently provide data services for CFD software credibility evaluation or related research.

In an approach to post-silicon analog design verification and validation, a method includes receiving a recovered layout and a golden data for a design; extracting a recovered netlist from the recovered layout and a golden netlist from the golden data; converting the recovered netlist into a recovered graph and the golden netlist into a golden graph; partitioning the recovered graph and the golden graph; and determining an assurance metric by comparing the recovered graph and the golden graph.

A system and method for a dynamic-link verification process between an electronic device and a transaction or event. The first step is engagement by a mobile electronic device with an initiator that is linked with a specific verification event that triggers a text message to auto-populate on a mobile electronic device. The message comprising metadata about the user and the event or transaction. The second step is for the electronic device to send the auto-populated message to a message gateway thus initiating the verification of the user. The message gateway works with a management service and one or more databases to verify the identity and other aspects of the user based on instructions provided by the event host. Additionally, configurable access tokens may be generated for each verified user wherein the access tokens provide access to an event or controlled physical location based on the configuration.

In an integrated circuit (IC) analysis, a reference IC layout is stored. Instructions are readable and executable by an electronic processor to perform an IC analysis method, including: receiving layer images of a physical IC; extracting polygons depicted in the layer images; detecting errors in the physical IC by applying homeomorphic error detection to compare the extracted polygons with polygons of the reference IC layout; and displaying the detected errors on the display. The detecting of errors may include detecting an error comprising a topological inequivalence between an extracted polygon or pair of polygons and a polygon or pair of polygons of the reference IC layout. The detecting of errors may include detecting an error comprising a topological coverage error.

The method disclosed in the present invention for standardizing the storage of CFD verification and confirmation case data includes case data organization, case data collation standards, and case data storage standards; the case data collation standards include case data naming standards, case description file compilation standards, self-description file definition standards, computational grid data collation standards, computational result data collation standards, and test result data collation standards; the case data storage standards are based on the data output by the case data collation standards, using a hierarchical tree-like organizational structure that is convenient for domestic users to use, and enter the case database from the perspectives of newly created cases, basic properties, case descriptions, comparable data, extraction tools, and related documents. The technical solution provided by the present invention standardizes and ensures the quality of submitted case data, solving the problem of incomplete case data and lack of availability during the construction of a CFD verification and confirmation case library.

The invention relates to the technical field of data security, in particular to a transaction data authenticity verification and verification method for a data platform, and the method comprises the steps: obtaining transaction voucher data of each entity through a block chain authority node; constructing a periodic fluctuation function according to periodic characteristics of renewable resource transactions; calculating a transportation fluctuation coefficient according to the characteristics of the transportation information in the transaction, and calculating an authenticity coefficient in combination with a periodic fluctuation function; and the transaction data uploaded to the block chain is effectively verified through the authenticity coefficient, so that the authenticity of the data is ensured. In order to prevent a certain node from acquiring all transaction information in the block chain to cause security risks, the invention aims to provide a mode which can verify the authenticity of the transaction data and also can guarantee the security of the transaction information on the chain.

One of the technical solutions of the present application is to provide a requirement analysis system in ship design. Another technical solution of the present application is to provide a requirement analysis method in ship design. The present application comprehensively uses MBSE, DoDAF and ontology technology to provide a requirement analysis system and method for ship design, fills the blank of actual requirement analysis oriented to task scene, and improves the systematization, completeness, rationality, standardization, consistency and traceability of ship requirements. The present application can improve the technical index requirements of ship equipment, provide reliable basis for subsequent design, analysis, verification and confirmation work, is beneficial to improve the satisfaction degree of ship overall scheme to actual requirements, and further improves the overall efficiency of ship equipment. The present application has important significance for improving the positive design level of ship equipment.

The deployment of large language model (LLM) and retrieval-augmented generation (RAG) systems in industrial automation environments present unique technical challenges that are not adequately addressed by conventional software validation approaches. A computing system can define a comprehensive architecture with cross-validation methodologies that can perform systematic detection of complex failure modes that might be missed by conventional testing approaches, while providing the reliability, safety, and real-time performance characteristics essential for successful deployment of LLM and RAG systems in industrial automation environments.