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The paper presents a flexible artificial neural network (ANN) model, in order to support modifications of a complex input-output function that describes the catalyst monitoring process of a multi-tube reactor. The goal is to obtain a good accuracy of the predicted data by using an optimal ANN architecture and well-suited delay vectors. The research targets(More)
The paper presents aspects of knowledge assessment in the framework of adaptive e-learning systems, focussing on aspect related to self-testing, as a way of providing the input necessary for both system adaptation and user informed decisions. A model of upward propagation of evaluation credits and downward propagation of validation and acceptance is(More)
The paper presents an image-oriented description of artificial and biological nanostructured surfaces, with applicability to the functional characterization of atom neighborhoods at the surface of proteins. The property which is considered is the hydrophobicity around each surface atom. The actual hydrophobicity distribution on the atoms that form an atom's(More)
Intelligent e-learning environments (ILE) can increase the attractivity of e-learning systems and their teaching efficiency by adapting to each learner profile (LP) and by providing multiple support to the tutor. ILE components guide the trainee through the learning process, offer a platform for co-operative learning and knowledge discovery, and customize(More)
The paper presents a classification of the protein surface atom neighbourhoods from the hydrophobicity perspective. Hydrophobicity is the property which is considered around each surface atom. The actual hydrophobicity distribution on the atoms that form an atom's vicinity is replaced by an equivalent hydrophobicity density distribution, computed in a(More)