Pattern Recognition for Nondestructive Evaluation

The issues involved in automating nondestructive evaluation (NDE) techniques are outlined. Attention is given to research focused on the application of machine learning techniques to the construction and maintenance of knowledge-based systems which are capable of evaluating the readings from nondestructive tests that have been performed on aircraft components. Preliminary results obtained from this research are described. In particular, the authors discuss the application of a symbolic machine learning algorithm, ID3, to the NDE problem. ID3 has been used by Douglas Aircraft to classify defects in sets of standard NDE reference blocks. Based on the preliminary results, a need for an improved method of distinguishing features in the test waveforms is identified. The authors also outline a feature extraction approach from pattern recognition, called scale-space filtering, which can be used to preprocess data for input into a classification algorithm such as ID3

Production and ecosystem structure in cold‐core vs. warm‐core eddies: Implications for the zooplankton isoscape and rock lobster larvae

Anticyclonic (warm-core) mesoscale eddies (WCEs) in the Eastern Indian Ocean carry higher surface chlorophyll signatures than cyclonic (cold-core) eddies (CCEs). Paradoxically, WCEs host rock lobster larvae (phyllosomas) with lower lipid stores and protein reserves than phyllosomas in CCEs, suggesting a poorer nutritional status. We assess primary productivity and zooplankton isotopic data from eight eddies across four research voyages (2003–2011) to determine how this contradiction might occur. We find that WCEs and CCEs are equally productive per unit chlorophyll a, but depth-integrated primary production (PP) is greater in eddies with shallower mixed layers (MLs), especially in CCEs. MLs tend to be shallower in CCEs than in WCEs because the pycnocline is closer to the surface. This, in combination with stronger stratification in CCE euphotic zones than those of WCEs, supports greater flagellate and dinoflagellate populations in CCEs. These phytoplankton provide high-quality nutrition for zooplankton, which feed on average ~ 0.6 trophic level lower in CCEs with the shallowest MLs, accumulating high lipid stores. Conversely, WCEs have, on average, ~ 70 m deeper MLs than CCEs, and host a phytoplankton community with more diatoms. Diatoms provide lower quality food for zooplankton, and zooplankton lipid stores in WCEs decline with trophic level, and possibly, with time after initial (or seasonal) nutrient injection. As a result, phyllosomas in CCEs have higher energy and lipid content than those in warm-core eddies. The resolution of the paradox, therefore, is that the higher surface chlorophyll signatures of WCEs are not representative of the nutritional value of the prey field of the phyllosoma. We also conclude that interannual variations of mixed layer depth occur at a regional scale, controlling PP