7 results about "Verification and validation" patented technology

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.

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.

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.