A computer-implemented method of machine-learning is described that includes obtaining a dataset of virtual scenes. The dataset of virtual scenes belongs to a first domain. The method further includes obtaining a test dataset of real scenes. The test dataset belongs to a second domain. The method further includes determining a third domain. The third domain is closer to the second domain than the first domain in terms of data distributions. The method further includes learning a domain-adaptive neural network based on the third domain. The domain-adaptive neural network is a neural network configured for inference of spatially reconfigurable objects in a real scene. Such a method constitutes an improved method of machine learning with a dataset of scenes including spatially reconfigurable objects.

A device receives an infrastructure design document that represents a network infrastructure design. The device causes the infrastructure design document to be displayed via a first interface of a geographic information system (GIS) tool that is to be used during an inspection of a site, where the inspection includes inspecting structural components that are to support equipment of a network. The device receives, from a user device, feedback data that is based on the inspection. The device causes the feedback data to be integrated into the GIS tool. The device receives, from another user device, instructions that are to be used to update the infrastructure design document. The device updates the infrastructure design document based on the set of instructions and performs actions that allow the infrastructure design document to be used when implementing the network infrastructure design.

Disclosed are techniques for performing a flow simulation that include storing in a memory state vectors for a plurality of voxels, the state vectors comprising a plurality of entries that correspond to particular momentum states of a plurality of possible momentum states at a voxel. The techniques also include storing in a memory a representation of at least one surface and performing interaction operations on the state vectors, the interaction operations modelling interactions between elements of different momentum states. The techniques also include performing surface interaction operations which model interactions between the surface and elements of at least one voxel near the surface, including modeling a to wall shear stress direction that is not parallel to a flow velocity direction and performing move operations on the state vectors to reflect movement of elements to new voxels.

An engineering support system that supports engineering of a process control system, includes: a storage; and a processor connected to the storage and that: transforms design drawings into semantic models and outputs the semantic models to the storage; and generates a combined semantic model by combining the semantic models based on a degree of similarity among the semantic models and outputs the combined semantic model to the storage, wherein each of the semantic models is expressed by first information indicating elements included in the design drawings and second information indicating a relationship between the elements.

Methods and systems are described to efficiently identify the potential for failures in integrated circuits (ICs) caused by glitches. In an IC based on synchronous operation, the operation of the multiplicity of inputs, storage elements and observed outputs in said IC are synchronized to one or more clocks that determine the specific times at which inputs change, outputs are observed, and stored values are updated. Almost all ICs are based on synchronous operation. When input values to a logic circuit in an IC change, the effects of said changes propagate through paths in said logic circuit in a delayed manner such that each of said paths may have a different delay. Said different delays can cause a wire in a logic circuit to have transient values (termed glitch) before settling to a final value consistent with the input values being applied to said logic circuit. An IC is likely to function erroneously, referred to as having a glitch failure, when a glitch value is observed at an output or captured by a storage element. Glitch failures are difficult and expensive to diagnose in a manufactured IC. To raise the productivity of IC development, it is imperative that any potential glitch failure in an IC be detected prior to manufacture. Said detection is hard because a typical IC has a very large number of logic circuits to analyze for glitch failure. To be practical, said analysis must have high performance and high accuracy. Said high performance requiring that said analysis should complete in acceptable run time even for the largest ICs. Said high accuracy requires that said analysis should identify all potential for glitch failure (100% recall), and minimize the number of logic circuits erroneously reported as having glitch failure potential (high precision). Whereas the glitch phenomenon, the potential for glitch failure and methods for detecting glitch failures in pre-manufacture IC models are well known, achievement of high performance with high accuracy has not yet been addressed in prior art. Whereas conventional methods for glitch checking are inefficient and insufficiently accurate, the methods and systems described in the present invention achieve new levels of performance, scalability and accuracy in said detection of glitch failures in an IC. Said methods and systems are based on a novel dissection of glitch-checking requirements into a multiplicity of individual steps, which said steps executed in a systematic sequence deliver high performance and accuracy.

The invention relates to a method for simulation-based analysis and/or optimization of a motor vehicle, preferably having the following working steps: simulating (SIOI) a driving operation of the motor vehicle (I) on the basis of a model (M) with at least one manipulated variable for acquiring values of at least one simulated variable which is suitable for characterizing an overall vehicle behaviour, in particular a driving capability, of the motor vehicle (I), wherein the model has at least one partial model, in particular a torque model, and wherein the at least one partial model is based on a function and preferably characterizes the operation of at least one component, in particular of an internal combustion engine of the motor vehicle (I); andoutputting (S I03) the values of the at least one simulated variable.

The present invention is a computer-implemented method for designing a drivetrain using computer aided engineering. The method comprises the steps of: a) receiving a selection of a certification test from a plurality of certification tests; b) receiving a parametric description of the drivetrain; c) receiving a selection of one or more analysis types appropriate for the selected certification test and the parametric description; d) providing a certification test model of the drivetrain based on the selected certification test, the parametric description, and the one or more analysis types; e) simulating performance of the drivetrain using the certification test model; and f) determining an indication of compliance of the drivetrain with the certification test based on the simulated performance.

A global computer aided engineering (CAE) model representing an electronic product that contains solder joints and an individual detailed solder joint model are received. The solder joint model can include a solder ball, one or more metal pads, a portion of printed circuit board, and a portion of semiconductor chip component. The global CAE model includes locations of the solder joints to be evaluated in a drop test simulation. The solder joint model is replicated at each location to create a local CAE model via a geometric relationship between the global CAE model and the local CAE model. Simulated physical behaviors of the product under a design condition are obtained in a co-simulation using the global CAE model in a first time scale and the local CAE model in a second time scale. Simulated physical behaviors are periodically synchronized based on kinematic and force constraints.