Very Deep Convolutional Neural Networks for Robust Speech Recognition

This paper describes the extension and optimization of our previous work on very deep convolutional neural networks (CNNs) for effective recognition of noisy speech in the Aurora 4 task. The appropriate number of convolutional layers, the sizes of the filters, pooling operations and input feature maps are all modified: the filter and pooling sizes are reduced and dimensions of input feature maps are extended to allow adding more convolutional layers. Furthermore appropriate input padding and input feature map selection strategies are developed. In addition, an adaptation framework using joint training of very deep CNN with auxiliary features i-vector and fMLLR features is developed. These modifications give substantial word error rate reductions over the standard CNN used as baseline. Finally the very deep CNN is combined with an LSTM-RNN acoustic model and it is shown that state-level weighted log likelihood score combination in a joint acoustic model decoding scheme is very effective. On the Aurora 4 task, the very deep CNN achieves a WER of 8.81%, further 7.99% with auxiliary feature joint training, and 7.09% with LSTM-RNN joint decoding.Comment: accepted by SLT 201

Bell violation for unknown continuous-variable states

We describe a new Bell test for two-particle entangled systems that engages an unbounded continuous variable. The continuous variable state is allowed to be arbitrary and inaccessible to direct measurements. A systematic method is introduced to perform the required measurements indirectly. Our results provide new perspectives on both the study of local realistic theory for continuous-variable systems and on the nonlocal control theory of quantum information.Comment: 8 pages, published versio

Anosmia and Ageusia as the Only Indicators of Coronavirus Disease 2019 (COVID-19)

The patient is a 60-year-old woman with a history of vertigo and seasonal allergies who presented to the hospital with the chief complaint of headache. Radiological findings were negative for intracranial abnormalities. The headache was due to trigeminal neuralgia. She had concurrent complaints of anosmia and ageusia without fever, respiratory symptoms, or obvious risk factors. However, it was determined to test the patient for coronavirus disease 2019 (COVID-19) infection despite extremely low clinical suspicion. Unfortunately, she was found to be COVID-19 positive after she was discharged from the hospital while she remained asymptomatic. There is currently a lack of published case reports describing COVID-19 patients with the sole symptoms of anosmia and ageusia in the United States of America

Polyisoprene Captured Sulfur Nanocomposite Materials for High-Areal-Capacity Lithium Sulfur Battery

A polyisoprene-sulfur (PIPS) copolymer and nano sulfur composite material (90 wt % sulfur) is synthesized through inverse vulcanization of PIP polymer with micrometer-sized sulfur particles for high-areal-capacity lithium sulfur batteries. The polycrystalline structure and nanodomain nature of the copolymer are revealed through high-resolution transmission electron microscopy (HRTEM). PIP polymer is also used as binders for the electrode to further capture the dissovlved polysulfides. A high areal capacity of ca. 7.0 mAh/cm2 and stable cycling are achieved based on the PIPS nanosulfur composite with a PIP binder, crucial to commercialization of lithium sulfur batteries. The chemical confinement both at material and electrode level alleviates the diffusion of polysulfides and the shuttle effect. The sulfur electrodes, both fresh and cycled, are analyzed through scanning electron microscopy (SEM). This approach enables scalable material production and high sulfur utilization at the cell level

Mode dispersion and delay characteristics of optical waveguides using equivalent TL circuits

A new analysis leading to an exact and efficient algorithm is presented for calculating directly and without numerical differentiation the mode dispersion characteristics of cylindrical dielectric waveguides of arbitrary refractive-index profile. The new algorithm is based on the equivalent transmission-line (T-L) technique. From Maxwell's equations, we derive an equivalent T-L circuit for a cylindrical dielectric waveguide. Based on the TL-circuit model we derive exact analytic formulas for a recursive algorithm which allows direct calculation of mode delay and dispersion. We demonstrate this technique by calculating the fundamental mode dispersion for step, triangular, and linear chirp optical fiber refractive index profiles. The accuracy of the numerical results is also examined. The proposed algorithm computes dispersion directly from the propagation constant without the need for curve fitting and subsequent successive numerical differentiation. It is exact, rapidly convergent, and it results in savings for both storage memory and computing time

Construction of nested space-filling designs

New types of designs called nested space-filling designs have been proposed for conducting multiple computer experiments with different levels of accuracy. In this article, we develop several approaches to constructing such designs. The development of these methods also leads to the introduction of several new discrete mathematics concepts, including nested orthogonal arrays and nested difference matrices.Comment: Published in at http://dx.doi.org/10.1214/09-AOS690 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org