133 research outputs found

    The impact of thermal degradation on electrical machine winding insulation

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    Quantum optical coherence tomography with dispersion cancellation

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    We propose a new technique, called quantum optical coherence tomography (QOCT), for carrying out tomographic measurements with dispersion-cancelled resolution. The technique can also be used to extract the frequency-dependent refractive index of the medium. QOCT makes use of a two-photon interferometer in which a swept delay permits a coincidence interferogram to be traced. The technique bears a resemblance to classical optical coherence tomography (OCT). However, it makes use of a nonclassical entangled twin-photon light source that permits measurements to be made at depths greater than those accessible via OCT, which suffers from the deleterious effects of sample dispersion. Aside from the dispersion cancellation, QOCT offers higher sensitivity than OCT as well as an enhancement of resolution by a factor of 2 for the same source bandwidth. QOCT and OCT are compared using an idealized sample.Comment: 19 pages, 4 figure

    Sapling size influences shade tolerance ranking among southern boreal tree species

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    1 Traditional rankings of shade tolerance of trees make little reference to individual size. However, greater respiratory loads with increasing sapling size imply that larger individuals will be less able to tolerate shade than smaller individuals of the same species and that there may be shifts among species in shade tolerance with size. 2 We tested this hypothesis using maximum likelihood estimation to develop individual-tree-based models of the probability of mortality as a function of recent growth rate for seven species: trembling aspen, paper birch, yellow birch, mountain maple, white spruce, balsam fir and eastern white cedar. 3 Shade tolerance of small individuals, as quantified by risk of mortality at low growth, was mostly consistent with traditional shade tolerance rankings such that cedar > balsam fir > white spruce > yellow birch > mountain maple = paper birch > aspen. 4 Differences in growth-dependent mortality were greatest between species in the smallest size classes. With increasing size, a reduced tolerance to shade was observed for all species except trembling aspen and thus species tended to converge in shade tolerance with size. At a given level of radial growth larger trees, apart from aspen, had a higher probability of mortality than smaller trees. 5 Successional processes associated with shade tolerance may thus be most important in the seedling stage and decrease with ontogeny

    Modeling body size evolution in Felidae under alternative phylogenetic hypotheses

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    The use of phylogenetic comparative methods in ecological research has advanced during the last twenty years, mainly due to accurate phylogenetic reconstructions based on molecular data and computational and statistical advances. We used phylogenetic correlograms and phylogenetic eigenvector regression (PVR) to model body size evolution in 35 worldwide Felidae (Mammalia, Carnivora) species using two alternative phylogenies and published body size data. The purpose was not to contrast the phylogenetic hypotheses but to evaluate how analyses of body size evolution patterns can be affected by the phylogeny used for comparative analyses (CA). Both phylogenies produced a strong phylogenetic pattern, with closely related species having similar body sizes and the similarity decreasing with increasing distances in time. The PVR explained 65% to 67% of body size variation and all Moran's I values for the PVR residuals were non-significant, indicating that both these models explained phylogenetic structures in trait variation. Even though our results did not suggest that any phylogeny can be used for CA with the same power, or that “good” phylogenies are unnecessary for the correct interpretation of the evolutionary dynamics of ecological, biogeographical, physiological or behavioral patterns, it does suggest that developments in CA can, and indeed should, proceed without waiting for perfect and fully resolved phylogenies

    Evolutionary Multi-objective Optimization for Simultaneous Generation of Signal-Type and Symbol-Type Representations

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    It has been a controversial issue in the research of cognitive science and artificial intelligence whether signal-type representations (typically connectionist networks) or symbol-type representations (e.g., semantic networks, production systems) should be used. Meanwhile, it has also been recognized that both types of information representations might exist in the human brain. In addition, symbol-type representations are often very helpful in gaining insights into unknown systems. For these reasons, comprehensible symbolic rules need to be extracted from trained neural networks. In this paper, an evolutionary multi-objective algorithm is employed to generate multiple models that facilitate the generation of signal-type and symbol-type representations simultaneously. It is argued that one main difference between signal-type and symbol-type representations lies in the fact that the signal-type representations are models of a higher complexity (fine representation), whereas symbol-type representations are models of a lower complexity (coarse representation). Thus, by generating models with a spectrum of model complexity, we are able to obtain a population of models of both signal-type and symbol-type quality, although certain post-processing is needed to get a fully symbol-type representation. An illustrative example is given on generating neural networks for the breast cancer diagnosis benchmark problem. © Springer-Verlag Berlin Heidelberg 2005
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