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Collaborative work with software models - industrial experience and requirements

When the initial problems of introducing and adopting model-driven development in a company have been handled, we want to go to work. That means that we have to supply our team of developers with a development environment and tools and processes that allow them to work efficiently. In many cases the team would like to work with models as if it was "just another programming language" and use the sa

Biosensor systems for blood lactate monitoring

Enzyme based biosensor systems for ex vivo blood lactate monitoring were developed. The first approach utilised an immobilised enzyme reactor incorporated in a flow system and the main objectives were integration of sampling, sample handling, analysis, control and calibration. The flow system comprised a double lumen catheter for continuous sampling and heparinisation of blood, a dialysis unit for

Spike-Feature Based Estimation of Electrode Position in Extracellular Neural Recordings

Detecting and sorting spikes in extracellular neural recordings are common procedures in assessing the activity of individual neurons. In chronic recordings, passive electrode movements introduce changes in the shape of detected spike waveforms, and may thus lead to problems with identification and tracking of spikes recorded at separate instances in time, which is an important step in long-term m

Learning and memory in moths - plasticity in behaviour and neurophysiology

The moth, Spodoptera littoralis, was demonstrated to be a new model system for studying mechanisms underlying odour conditioning. In the experiments a restrained moth was trained to learn an association between a conditioned stimulus (CS) and an unconditioned stimulus (US). A proboscis extension reflex (PER) elicited by the conditioned odour was observed after learning. In paper I, an odour-sucros

Investigating multilingual dependency parsing

In this paper, we describe a system for the CoNLL-X shared task of multilingual dependency parsing. It uses a baseline Nivre’s parser (Nivre, 2003) that first identifies the parse actions and then labels the dependency arcs. These two steps are implemented as SVM classifiers using LIBSVM. Features take into account the static context as well as relations dynamically built during parsing. We experi