A target system is coupled to a diagnosis engine that uses a lumped parameter model of the system for diagnosis. A proximity search in is performed in a computer-aided design model of the system to find groups of components that may be affected by resistive or parasitic interactions between the individual components in the groups. The lumped parameter model is augmented by adding elements that emulate the resistive or parasitic interactions between the individual components in the groups. The augmented lumped model is used by the diagnosis engine to perform diagnosis on the system.

Methods and systems for accelerated training of a machine learning based model for semiconductor applications are provided. One method for training a machine learning based model includes acquiring information for non-nominal instances of specimen(s) on which a process is performed. The machine learning based model is configured for performing simulation(s) for the specimens. The machine learning based model is trained with only information for nominal instances of additional specimen(s). The method also includes re-training the machine learning based model with the information for the non-nominal instances of the specimen(s) thereby performing transfer learning of the information for the non-nominal instances of the specimen(s) to the machine learning based model.

An information processing apparatus (10) is for supporting work by a user who uses drawings for a plant. The information processing apparatus (10) includes a controller (15). The controller (15) is configured to convert a drawing including elements configuring the plant into an abstract model represented by element information indicating the elements and connection information indicating a connection relationship between the elements. The controller (15) is configured to generate display information, when it is judged that a difference exists between one abstract model based on one drawing and another abstract model based on another drawing, for displaying the differing portion in a different form than another portion.

Systems and methods are provided for requirements engineering, and may include: receiving as input, time series data from at least one of a simulation of a vehicle run on a simulation system, or from the vehicle in operation; a requirements monitoring system checking to determine whether a plurality of requirements for operation of the vehicle are met, wherein the requirements are expressed in signal temporal logic form and a requirement includes at least an associated minimal sampling rate and a filtering policy applicable to the requirement; determining a quantitative conformance for each of selected requirements of the plurality of requirements; and add requirements to a verified requirements set based on the qualitative conformance of the requirements.

Systems and methods are provided for requirements engineering, and may include: receiving as input, time series data from at least one of a simulation of a vehicle run on a simulation system, or from the vehicle in operation; a requirements monitoring system checking to determine whether a plurality of requirements for operation of the vehicle are met, wherein the requirements are expressed in signal temporal logic form and a requirement includes at least an associated minimal sampling rate and a filtering policy applicable to the requirement; determining a quantitative conformance for each of selected requirements of the plurality of requirements; and add requirements to a verified requirements set based on the qualitative conformance of the requirements.

Computer-implemented methods and apparatus are provided for predicting/estimating (i) a non-equilibrium viscosity for at least one given time point in a given temperature profile for a given glass composition, (ii) at least one temperature profile that will provide a given non-equilibrium viscosity for a given glass composition, or (iii) at least one glass composition that will provide a given non-equilibrium viscosity for a given time point in a given temperature profile. The methods and apparatus can be used to predict/estimate stress relaxation in a glass article during forming as well as compaction, stress relaxation, and/or thermal sag or thermal creep of a glass article when the article is subjected to one or more post-forming thermal treatments.

Computer-implemented methods and apparatus are provided for predicting/estimating (i) a non-equilibrium viscosity for at least one given time point in a given temperature profile for a given glass composition, (ii) at least one temperature profile that will provide a given non-equilibrium viscosity for a given glass composition, or (iii) at least one glass composition that will provide a given non-equilibrium viscosity for a given time point in a given temperature profile. The methods and apparatus can be used to predict/estimate stress relaxation in a glass article during forming as well as compaction, stress relaxation, and/or thermal sag or thermal creep of a glass article when the article is subjected to one or more post-forming thermal treatments.

Methods and systems are provided for generating an interactive simulation representing one or more assets based on one or more asset records. Based on information from asset records stored at a database system of a cloud-based computing system, an asset simulator module, executed at a cloud-based computing system, can generate one or more simulated representations of the assets. A simulator application executed at the cloud-based computing system can augment the simulated representations of the assets with (at least) additional information from the asset records stored in the database system, and generate a user interface that presents an interactive simulation of the assets. The user interface can include the simulated representations of the assets with the additional information from the asset records stored in the database system.

Methods and systems are provided for generating an interactive simulation representing one or more assets based on one or more asset records. Based on information from asset records stored at a database system of a cloud-based computing system, an asset simulator module, executed at a cloud-based computing system, can generate one or more simulated representations of the assets. A simulator application executed at the cloud-based computing system can augment the simulated representations of the assets with (at least) additional information from the asset records stored in the database system, and generate a user interface that presents an interactive simulation of the assets. The user interface can include the simulated representations of the assets with the additional information from the asset records stored in the database system.

Described herein are a system and methods for efficiently using depth and image information for a space to generate a 3D representation of that space. In some embodiments, an indication of one or more points is received with respect to image information, which is then mapped to corresponding points within depth information. A boundary may then be calculated to be associated with each of the points based on the depth information at, and surrounding, each point. Each of the boundaries are extended outward until junctions are identified as bounding the boundaries in a direction. The system may determine whether the process is complete or not based on whether any of the calculated boundaries are currently unlimited in extent in any direction. Once the system determines that each of the boundaries is limited in extent, a 3D representation of the space may be generated based on the identified junctions and/or boundaries.