15,996 research outputs found
Backscatter Transponder Based on Frequency Selective Surface for FMCW Radar Applications
This paper describes an actively-controlled frequency selective surface (FSS) to implement a backscatter transponder. The FSS is composed by dipoles loaded with switching PIN diodes. The transponder exploits the change in the radar cross section (RCS) of the FSS with the bias of the diodes to modulate the backscattered response of the tag to the FMCW radar. The basic operation theory of the system is explained here. An experimental setup based on a commercial X-band FMCW radar working as a reader is proposed to measure the transponders. The transponder response can be distinguished from the interference of non-modulated clutter, modulating the transponder’s RCS. Some FSS with different number of dipoles are studied, as a proof of concept. Experimental results at several distances are provided
The Site-Diluted Ising Model in Four Dimension
In the literature, there are five distinct, fragmented sets of analytic
predictions for the scaling behaviour at the phase transition in the
random-site Ising model in four dimensions. Here, the scaling relations for
logarithmic corrections are used to complete the scaling pictures for each set.
A numerical approach is then used to confirm the leading scaling picture coming
from these predictions and to discriminate between them at the level of
logarithmic corrections.Comment: 15 pages, 5 ps figures. Accepted for publication in Phys. Rev.
Towards an Unsupervised Speaking Style Voice Building Framework:Multi-Style Speaker Diarization
Tiling Spaces are Inverse Limits
Let M be an arbitrary Riemannian homogeneous space, and let Omega be a space
of tilings of M, with finite local complexity (relative to some symmetry group
Gamma) and closed in the natural topology. Then Omega is the inverse limit of a
sequence of compact finite-dimensional branched manifolds. The branched
manifolds are (finite) unions of cells, constructed from the tiles themselves
and the group Gamma. This result extends previous results of Anderson and
Putnam, of Ormes, Radin and Sadun, of Bellissard, Benedetti and Gambaudo, and
of G\"ahler. In particular, the construction in this paper is a natural
generalization of G\"ahler's.Comment: Latex, 6 pages, including one embedded figur
Semi-Supervised Deep Learning for Fully Convolutional Networks
Deep learning usually requires large amounts of labeled training data, but
annotating data is costly and tedious. The framework of semi-supervised
learning provides the means to use both labeled data and arbitrary amounts of
unlabeled data for training. Recently, semi-supervised deep learning has been
intensively studied for standard CNN architectures. However, Fully
Convolutional Networks (FCNs) set the state-of-the-art for many image
segmentation tasks. To the best of our knowledge, there is no existing
semi-supervised learning method for such FCNs yet. We lift the concept of
auxiliary manifold embedding for semi-supervised learning to FCNs with the help
of Random Feature Embedding. In our experiments on the challenging task of MS
Lesion Segmentation, we leverage the proposed framework for the purpose of
domain adaptation and report substantial improvements over the baseline model.Comment: 9 pages, 6 figure
Impact of DM direct searches and the LHC analyses on branon phenomenology
Dark Matter direct detection experiments are able to exclude interesting
parameter space regions of particle models which predict an important amount of
thermal relics. We use recent data to constrain the branon model and to compute
the region that is favored by CDMS measurements. Within this work, we also
update present colliders constraints with new studies coming from the LHC.
Despite the present low luminosity, it is remarkable that for heavy branons,
CMS and ATLAS measurements are already more constraining than previous analyses
performed with TEVATRON and LEP data.Comment: 17 pages, 2 figure
Universal Amplitude Ratios in the Ising Model in Three Dimensions
We use a high-precision Monte Carlo simulation to determine the universal
specific-heat amplitude ratio A+/A- in the three-dimensional Ising model via
the impact angle \phi of complex temperature zeros. We also measure the
correlation-length critical exponent \nu from finite-size scaling, and the
specific-heat exponent \alpha through hyperscaling. Extrapolations to the
thermodynamic limit yield \phi = 59.2(1.0) degrees, A+/A- = 0.56(3), \nu =
0.63048(32) and \alpha = 0.1086(10). These results are compatible with some
previous estimates from a variety of sources and rule out recently conjectured
exact values.Comment: 17 pages, 5 figure
- …