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Chaining is a type of intervention that aims to create associations between behaviors in a behavior chain. [1] A behavior chain is a sequence of behaviors that happen in a particular order where the outcome of the previous step in the chain serves as a signal to begin the next step in the chain.
Pipeline of Apertium machine translation system. This is an overall, step-by-step view how Apertium works. The diagram displays the steps that Apertium takes to translate a source-language text (the text we want to translate) into a target-language text (the translated text). Source language text is passed into Apertium for translation.
Object-oriented applications contain complex webs of interrelated objects. Objects are linked to each other by one object either owning or containing another object or holding a reference to another object. This web of objects is called an object graph and it is the more abstract structure that can be used in discussing an application's state.
In Euclidean geometry, a translation is a geometric transformation that moves every point of a figure, shape or space by the same distance in a given direction. A translation can also be interpreted as the addition of a constant vector to every point, or as shifting the origin of the coordinate system. In a Euclidean space, any translation is ...
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In computer science, a rule-based system is a computer system in which domain-specific knowledge is represented in the form of rules and general-purpose reasoning is used to solve problems in the domain. Two different kinds of rule-based systems emerged within the field of artificial intelligence in the 1970s:
An object may be composed of components. A component is an object completely within the boundary of a containing object. A living thing may be an object, and is distinguished from non-living things by the designation of the latter as inanimate objects. Inanimate objects generally lack the capacity or desire to undertake actions, although humans ...
By 2020, the system had been replaced by another deep learning system based on a Transformer encoder and an RNN decoder. [10] GNMT improved on the quality of translation by applying an example-based (EBMT) machine translation method in which the system learns from millions of examples of language translation. [2]