Transfer Functions in Artificial Neural Networks - A Simulation-Based Tutorial

Artificial neural networks are based on computational units that resemble basic information processing properties of biological neurons in an abstract and simplified manner. Generally, these formal neurons model an input-output behaviour as it is also often used to characterize biological neurons. The neuron is treated as a black box; spatial extension and temporal dynamics present in biological neurons are most often neglected. Even though artificial neurons are simplified, they can show a variety of input-output relations, depending on the transfer functions they apply. This unit on transfer functions provides an overview of different transfer functions and offers a simulation that visualizes the input-output behaviour of an artificial neuron depending on the specific combination of transfer functions.

Learning Paradigms Exemplified by Virtual Experiments with Honey Bees

Learning is based on rules that can be elucidated by behavioural experiments. This article focuses on virtual experiments, in which non-associative learning (habituation, sensitization) and principles of associative learning (contiguity, inhibitory learning, generalization, overshadowing, positive and negative patterning) can be examined using 'virtual' honey bees in PER (Proboscis Reaction Extension) conditioning experiments. Users can develop experimental designs, simulate and document the experiments and find explanations and suggestions for the analysis of the learning experiments. The virtual experiments are based on video sequences and data from actual learning experiments. The bees' responses are determined by probability-based learning profiles.

aXess: an authoring tool for XML content management

The use of XML for representation of eLearning-content and for automatic generation of different kinds of teaching media from this material is with all its advantages nowadays stateof-the-art. In the last years there have been numerous projects that leveraged XML-based production environments. At the end of the financial advancement the created materials have to be maintained with limited (human) resources. In the majority of cases this is only possible, if the authors care for their teaching material without extensive IT-support. From our point of view there has so far been a lack of intuitive usable XML editors. The prototype of such an XML editor “aXess” is introduced with the intention to encourage a broad discussion about the required features to manage the content of eLearning-materials.