3,865 research outputs found

    Weighted Distance-Based Models for Ranking Data Using the R Package rankdist

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    rankdist is a recently developed R package which implements various distance-based ranking models. These models capture the occurring probability of rankings based on the distances between them. The package provides a framework for fitting and evaluating finite mixture of distance-based models. This paper also presents a new probability model for ranking data based on a new notion of weighted Kendall distance. The new model is flexible and more interpretable than the existing models. We show that the new model has an analytic form of the probability mass function and the maximum likelihood estimates of the model parameters can be obtained efficiently even for ranking involving a large number of objects

    Unsupervised Cross-lingual Image Captioning

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    Most recent image captioning works are conducted in English as the majority of image-caption datasets are in English. However, there are a large amount of non-native English speakers worldwide. Generating image captions in different languages is worth exploring. In this paper, we present a novel unsupervised method to generate image captions without using any caption corpus. Our method relies on 1) a cross-lingual auto-encoding, which learns the scene graph mapping function along with the scene graph encoders and sentence decoders on machine translation parallel corpora, and 2) an unsupervised feature mapping, which seeks to map the encoded scene graph features from image modality to sentence modality. By leveraging cross-lingual auto-encoding, cross-modal feature mapping, and adversarial learning, our method can learn an image captioner to generate captions in different languages. We verify the effectiveness of our proposed method on the Chinese image caption generation. The comparisons against several baseline methods demonstrate the effectiveness of our approach.Comment: 8 page

    Reprocessing and recycling of thermoset polymers based on bond exchange reaction

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    Recently, it has been reported that by properly catalytic controlled bond exchange reactions, thermoset polymers could be welded by simple heating. During the operation, polymer topology could be rearranged in complying the external deformation and release the internal stress, but the network integrity is maintained and the average functionality of polymer chains is unchanged. This novel technology also enables us to reprocess and recycle the thermoset polymers. In this study, we experimentally demonstrated that after being milled into pulverous state in microsize, the thermoset epoxy polymer with exchangeable bond could be welded and assembled again into integrity with regained mechanical properties comparable to a fresh bulk polymer. The detailed operation procedure, as well as the influence of pressure and heating time on the stretch ability of the recycled polymer sample, is demonstrated. Such an in-depth reprocessing routine could be repeated for multiple times in manufacturing complex objects and welding separated bulk polymers. Considering the efficient and robust welding effect among polymer particles, as well as the maintained merits of thermoset polymer as stress-bearing materials during the operation, this new strategy is more suitable to repair polymer structures in service and recycle the thermoset waste in most engineering applications

    Quantum Brownian Motion With Large Friction

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    Quantum Brownian motion in the strong friction limit is studied based on the exact path integral formulation of dissipative systems. In this limit the time-nonlocal reduced dynamics can be cast into an effective equation of motion, the quantum Smoluchowski equation. For strongly condensed phase environments it plays a similar role as master equations in the weak coupling range. Applications for chemical, mesoscopic, and soft matter systems are discussed and reveal the substantial role of quantum fluctuations.Comment: 11 pages, 6 figures, to appear in: Chaos: "100 years of Brownian motion

    Frictional drag between quantum wells mediated by phonon exchange

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    We use the Kubo formalism to evaluate the contribution of acoustic phonon exchange to the frictional drag between nearby two-dimensional electron systems. In the case of free phonons, we find a divergent drag rate (τD−1\tau_{D}^{-1}). However, τD−1\tau_{D}^{-1} becomes finite when phonon scattering from either lattice imperfections or electronic excitations is accounted for. In the case of GaAs quantum wells, we find that for a phonon mean free path ℓph\ell_{ph} smaller than a critical value, imperfection scattering dominates and the drag rate varies as ln(ℓph/d)ln (\ell_{ph}/d) over many orders of magnitude of the layer separation dd. When ℓph\ell_{ph} exceeds the critical value, the drag rate is dominated by coupling through an electron-phonon collective mode localized in the vicinity of the electron layers. We argue that the coupled electron-phonon mode may be observable for realistic parameters. Our theory is in good agreement with experimental results for the temperature, density, and dd-dependence of the drag rate.Comment: 45 pages, LaTeX, 8 postscript file figure
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