The ontological representation of learning objects is a way to deal with the interoperability and reusability of learning objects (including metadata) through providing a semantic...
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
This paper addresses a noise suppression problem, namely the estimation of non-stationary noise sequences. In this problem, we assume that non-stationary noise can be decomposed i...
In semantics-based component retrieval ontology is usually employed as the semantic basis for component representation and matching. Existing methods always assume that the ontolo...
— We propose a method for component-based software and system development, where the interoperability between the different components is given special consideration. The method ...