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Run-and-tumble motion is a movement pattern exhibited by certain bacteria and other microscopic agents. It consists of an alternating sequence of "runs" and "tumbles": during a run, the agent propels itself in a fixed (or slowly varying) direction, and during a tumble, it remains stationary while it reorients itself in preparation for the next run.
The client–server model is a distributed application structure that partitions tasks or workloads between the providers of a resource or service, called servers, and service requesters, called clients. [1] Often clients and servers communicate over a computer network on separate hardware, but both client and server may be on the same device.
The acronym GCM originally stood for General Circulation Model.Recently, a second meaning came into use, namely Global Climate Model.While these do not refer to the same thing, General Circulation Models are typically the tools used for modelling climate, and hence the two terms are sometimes used interchangeably.
For example, the trap instruction is one method of switching execution models. This difference is what distinguishes an API-invoked execution model, such as Pthreads, from a usual software library. Both Pthreads calls and software library calls are invoked via an API, but Pthreads behavior cannot be understood in terms of the language of the call.
Despite the fact that discriminative models do not need to model the distribution of the observed variables, they cannot generally express complex relationships between the observed and target variables. But in general, they don't necessarily perform better than generative models at classification and regression tasks. The two classes are seen ...
Ngspice supports parametric netlists (i.e. netlists can contain parameters and expressions). PSPICE compatible parametric macromodels, often released by manufacturers, can be imported as-is into the simulator.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
A dry run (or practice run) is a software testing process used to make sure that a system works correctly and will not result in severe failure. [1] For example, rsync, a utility for transferring and synchronizing data between networked computers or storage drives, has a "dry-run" option users can use to check that their command-line arguments are valid and to simulate what would happen when ...