Automatic classification of field-collected dinoflagellates by artificial neural network

Automatic taxonomic categorisation of 23 species of dinoflagellates was demonstrated using field-collected specimens. These dinoflagellates have been responsible for the majority of toxic and noxious phytoplankton blooms which have occurred in the coastal waters of the European Union in recent years and make severe impact on the aquaculture industry. The performance by human 'expert' ecologists/taxonomists in identifying these species was compared to that achieved by 2 artificial neural network classifiers (multilayer perceptron and radial basis function networks) and 2 other statistical techniques, k-Nearest Neighbour and Quadratic Discriminant Analysis. The neural network classifiers outperform the classical statistical techniques. Over extended trials, the human experts averaged 85% while the radial basis network achieved a best performance of 83%, the multilayer perceptron 66%, k-Nearest Neighbour 60%, and the Quadratic Discriminant Analysis 56%

Modeling and control of rotating stall and surge : an overview

Stable operation of both axial and radial compressors is constrained by rotating stall and surge. Developments in the understanding of the physics behind these instabilities, and ideas of how to stabilize the compressor system, have opened the door to a new era in the field of compressor control: so-called active control. The paper gives an overview of the current state of modeling and control of aerodynamic flow instabilities in axial and radial compressors. It discusses the differences between rotating stall and these compressors but focuses on active control systems applied in experimental studies. The evolution of models and control systems demonstrates that this research area is still developing, but models cannot yet describe all forms of instabilities encountered. Moreover, apart from a few exceptions, only proportional feedback controllers are currently used. As a result, future research has to concentrate on gaining additional insight into the mechanisms behind the flow instabilities and on how to incorporate this knowledge in a model. This will also be beneficial for the development of advanced model-based controllers