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Automatic item generation (AIG), or automated item generation, is a process linking psychometrics with computer programming. It uses a computer algorithm to automatically create test items that are the basic building blocks of a psychological test .
With the purchase of NeXT in late 1996, Apple developed a new operating system strategy based largely on the existing OPENSTEP for Mach platform. The new Rhapsody OS strategy was relatively simple; it retained most of OpenStep's existing object libraries under the name "Yellow Box", ported the existing GUI in OPENSTEP for Mach and made it look more Mac-like, ported several major APIs from the ...
Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.
The simulation model must be sufficiently faithful to the original, so that it behaves in practically the same way as the original brain. [118] Whole brain emulation is a type of brain simulation that is discussed in computational neuroscience and neuroinformatics , and for medical research purposes.
The difference stems from load commands that the dynamic linker, in previous Mac OS X versions, does not understand. Another significant change to the Mach-O format is the change in how the Link Edit tables (found in the __LINKEDIT section) function.
A canonical model is a design pattern used to communicate between different data formats. Essentially: create a data model which is a superset of all the others ("canonical"), and create a "translator" module or layer to/from which all existing modules exchange data with other modules. The canonical model acts as a middleman.
SIFT matching is done for a number of 2D images of a scene or object taken from different angles. This is used with bundle adjustment initialized from an essential matrix or trifocal tensor to build a sparse 3D model of the viewed scene and to simultaneously recover camera poses and calibration parameters. Then the position, orientation and ...
Prediction by partial matching (PPM) is an adaptive statistical data compression technique based on context modeling and prediction. PPM models use a set of previous symbols in the uncompressed symbol stream to predict the next symbol in the stream. PPM algorithms can also be used to cluster data into predicted groupings in cluster analysis.