2,109 research outputs found

    Tangibility and Memory in Abstract Landscapes

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    A stochastic network with mobile users in heavy traffic

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    We consider a stochastic network with mobile users in a heavy-traffic regime. We derive the scaling limit of the multi-dimensional queue length process and prove a form of spatial state space collapse. The proof exploits a recent result by Lambert and Simatos which provides a general principle to establish scaling limits of regenerative processes based on the convergence of their excursions. We also prove weak convergence of the sequences of stationary joint queue length distributions and stationary sojourn times.Comment: Final version accepted for publication in Queueing Systems, Theory and Application

    The absolute position of a resonance peak

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    It is common practice in scattering theory to correlate between the position of a resonance peak in the cross section and the real part of a complex energy of a pole of the scattering amplitude. In this work we show that the resonance peak position appears at the absolute value of the pole's complex energy rather than its real part. We further demonstrate that a local theory of resonances can still be used even in cases previously thought impossible

    Deep Learning of Sea Surface Temperature Patterns to Identify Ocean Extremes

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    We performed an out-of-distribution (OOD) analysis of ∼12,000,000 semi-independent 128 × 128 pixel2 sea surface temperature (SST) regions, which we define as cutouts, from all nighttime granules in the MODIS R2019 Level-2 public dataset to discover the most complex or extreme phenomena at the ocean’s surface. Our algorithm (ULMO) is a probabilistic autoencoder (PAE), which combines two deep learning modules: (1) an autoencoder, trained on ∼150,000 random cutouts from 2010, to represent any input cutout with a 512-dimensional latent vector akin to a (non-linear) Empirical Orthogonal Function (EOF) analysis; and (2) a normalizing flow, which maps the autoencoder’s latent space distribution onto an isotropic Gaussian manifold. From the latter, we calculated a log-likelihood (LL) value for each cutout and defined outlier cutouts to be those in the lowest 0.1% of the distribution. These exhibit large gradients and patterns characteristic of a highly dynamic ocean surface, and many are located within larger complexes whose unique dynamics warrant future analysis. Without guidance, ULMO consistently locates the outliers where the major western boundary currents separate from the continental margin. Prompted by these results, we began the process of exploring the fundamental patterns learned by ULMO thereby identifying several compelling examples. Future work may find that algorithms such as ULMO hold significant potential/promise to learn and derive other, not-yet-identified behaviors in the ocean from the many archives of satellite-derived SST fields. We see no impediment to applying them to other large remote-sensing datasets for ocean science (e.g., SSH and ocean color)

    Densidades, tamanho de grupo e reprodução de emas no Pantanal Sul.

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    Este estudo sobre a ecologia das emas no Pantanal foi uma primeira experiência na região, e teve o objetivo de avaliar as possibilidades de utilização da espécie nas fazendas do Pantanal da Nhecolândia. A população estimada, através de um levantamento aéreo, foi de 6.500 emas adultas, em todo o Pantanal. Na fazenda Nhumirim foram encontrados 73 grupos de emas durante o estudo, e o número de grupos variou ao longo do ano, de 2 a 17 indivíduos. A razão sexual foi de 1 macho para 3,6 fêmeas. Os ninhos foram feitos pelos machos, em áreas abertas e em áreas fechadas. Nos 2 anos do estudo foram encontrados 26 ninhos, e o número de ovos variou de 5 a 25. O principal predador dos ninhos foi o tatu-peba. A população de emas no Pantanal está bem conservada e existe possibilidade do uso sustentado da espécie.bitstream/item/37302/1/BP55.pd
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