The spatial distribution of the specific absorption rate (SAR) was measured in a full-scale model of man using implantable electric field probes. The model was exposed in the near-field of linear and aperture antennas at 350 MHz. Effects of the wave polarization, antenna position and antenna gain on the SAR distribution and the average SAR in the whole-body and body parts are reported.
We present a novel approach for learning embeddings of ALC knowledge base concepts. The embeddings reflect the semantics of the concepts in such a way that it is possible to compute an embedding of a complex concept from the embeddings of its parts by using appropriate neural constructors. Embeddings for different knowledge bases are vectors in a shared vector space, shaped in such a way that approximate subsumption checking for arbitrarily complex concepts can be done by the same neural network, called a reasoner head, for all the knowledge bases. To underline this unique property of enabling reasoning directly on embeddings, we call them reason-able embeddings. We report the results of experimental evaluation showing that the difference in reasoning performance between training a separate reasoner head for each ontology and using a shared reasoner head, is negligible.
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