6,733 research outputs found
Language Transfer of Audio Word2Vec: Learning Audio Segment Representations without Target Language Data
Audio Word2Vec offers vector representations of fixed dimensionality for
variable-length audio segments using Sequence-to-sequence Autoencoder (SA).
These vector representations are shown to describe the sequential phonetic
structures of the audio segments to a good degree, with real world applications
such as query-by-example Spoken Term Detection (STD). This paper examines the
capability of language transfer of Audio Word2Vec. We train SA from one
language (source language) and use it to extract the vector representation of
the audio segments of another language (target language). We found that SA can
still catch phonetic structure from the audio segments of the target language
if the source and target languages are similar. In query-by-example STD, we
obtain the vector representations from the SA learned from a large amount of
source language data, and found them surpass the representations from naive
encoder and SA directly learned from a small amount of target language data.
The result shows that it is possible to learn Audio Word2Vec model from
high-resource languages and use it on low-resource languages. This further
expands the usability of Audio Word2Vec.Comment: arXiv admin note: text overlap with arXiv:1603.0098
String Theory and Turbulence
We propose a string theory of turbulence that explains the Kolmogorov scaling
in 3+1 dimensions and the Kraichnan and Kolmogorov scalings in 2+1 dimensions.
This string theory of turbulence should be understood in light of the AdS/CFT
dictionary. Our argument is crucially based on the use of Migdal's loop
variables and the self-consistent solutions of Migdal's loop equations for
turbulence. In particular, there is an area law for turbulence in 2+1
dimensions related to the Kraichnan scaling.Comment: LaTeX; 15 pages, two figures; v.2: slight changes to text, footnotes
and references adde
Quantum Gravity and Turbulence
We apply recent advances in quantum gravity to the problem of turbulence.
Adopting the AdS/CFT approach we propose a string theory of turbulence that
explains the Kolmogorov scaling in 3+1 dimensions and the Kraichnan and
Kolmogorov scalings in 2+1 dimensions. In the gravitational context, turbulence
is intimately related to the properties of spacetime, or quantum, foam.Comment: 8 pages, LaTeX; Honorable Mention in the 2010 Gravity Research
Foundation Essay Contes
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Nearly 6.4 Million Californians Lacked Health Insurance in 2007 -- Recession Likely to Reverse Small Gains in Coverage
Summarizes findings from the California Health Interview Survey (CHIS) on trends in the state's uninsured rate, the underlying factors, and projected trends. Points to flaws in the eligibility rules for public coverage and outlines policy implications
Indoor Localization for Personalized Ambient Assisted Living of Multiple Users in Multi-Floor Smart Environments
This paper presents a multifunctional interdisciplinary framework that makes
four scientific contributions towards the development of personalized ambient
assisted living, with a specific focus to address the different and dynamic
needs of the diverse aging population in the future of smart living
environments. First, it presents a probabilistic reasoning-based mathematical
approach to model all possible forms of user interactions for any activity
arising from the user diversity of multiple users in such environments. Second,
it presents a system that uses this approach with a machine learning method to
model individual user profiles and user-specific user interactions for
detecting the dynamic indoor location of each specific user. Third, to address
the need to develop highly accurate indoor localization systems for increased
trust, reliance, and seamless user acceptance, the framework introduces a novel
methodology where two boosting approaches Gradient Boosting and the AdaBoost
algorithm are integrated and used on a decision tree-based learning model to
perform indoor localization. Fourth, the framework introduces two novel
functionalities to provide semantic context to indoor localization in terms of
detecting each user's floor-specific location as well as tracking whether a
specific user was located inside or outside a given spatial region in a
multi-floor-based indoor setting. These novel functionalities of the proposed
framework were tested on a dataset of localization-related Big Data collected
from 18 different users who navigated in 3 buildings consisting of 5 floors and
254 indoor spatial regions. The results show that this approach of indoor
localization for personalized AAL that models each specific user always
achieves higher accuracy as compared to the traditional approach of modeling an
average user
A Comparative Study of Dark Energy Constraints from Current Observational Data
We examine how dark energy constraints from current observational data depend
on the analysis methods used: the analysis of Type Ia supernovae (SNe Ia), and
that of galaxy clustering data. We generalize the flux-averaging analysis
method of SNe Ia to allow correlated errors of SNe Ia, in order to reduce the
systematic bias due to weak lensing of SNe Ia. We find that flux-averaging
leads to larger errors on dark energy and cosmological parameters if only SN Ia
data are used. When SN Ia data (the latest compilation by the SNLS team) are
combined with WMAP 7 year results (in terms of our Gaussian fits to the
probability distributions of the CMB shift parameters), the latest Hubble
constant (H_0) measurement using the Hubble Space Telescope (HST), and gamma
ray burst (GRB) data, flux-averaging of SNe Ia increases the concordance with
other data, and leads to significantly tighter constraints on the dark energy
density at z=1, and the cosmic curvature \Omega_k. The galaxy clustering
measurements of H(z=0.35)r_s(z_d) and r_s(z_d)/D_A(z=0.35) (where H(z) is the
Hubble parameter, D_A(z) is the angular diameter distance, and r_s(z_d) is the
sound horizon at the drag epoch) by Chuang & Wang (2011) are consistent with SN
Ia data, given the same pirors (CMB+H_0+GRB), and lead to significantly
improved dark energy constraints when combined. Current data are fully
consistent with a cosmological constant and a flat universe.Comment: 11 pages, 9 figures. Slightly revised version, to appear in PRD.
Supernova flux-averaging code available at
http://www.nhn.ou.edu/~wang/SNcode
Ignition and Front Propagation in Polymer Electrolyte Membrane Fuel Cells
Water produced in a Polymer Electrolyte Membrane (PEM) fuel cell enhances
membrane proton conductivity; this positive feedback loop can lead to current
ignition. Using a segmented anode fuel cell we study the effect of gas phase
convection and membrane diffusion of water on the spatiotemporal nonlinear
dynamics - localized ignition and front propagation - in the cell. Co-current
gas flow causes ignition at the cell outlet, and membrane diffusion causes the
front to slowly propagate to the inlet; counter-current flow causes ignition in
the interior of the cell, with the fronts subsequently spreading towards both
inlets. These instabilities critically affect fuel cell performance
Charmed Baryon Weak Decays with SU(3) Flavor Symmetry
We study the semileptonic and non-leptonic charmed baryon decays with
flavor symmetry, where the charmed baryons can be , , , or . With denoted as the baryon
octet (decuplet), we find that the
decays are forbidden, while the ,
, and decays are the only existing Cabibbo-allowed modes
for , , and , respectively. We predict the rarely studied
decays, such as and . For the observation, the doubly and triply charmed baryon decays of
, ,
, and are the favored Cabibbo-allowed decays,
which are accessible to the BESIII and LHCb experiments.Comment: 29 pages, no figure, a typo in the table correcte
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