667 research outputs found
Lempel-Ziv Parsing in External Memory
For decades, computing the LZ factorization (or LZ77 parsing) of a string has
been a requisite and computationally intensive step in many diverse
applications, including text indexing and data compression. Many algorithms for
LZ77 parsing have been discovered over the years; however, despite the
increasing need to apply LZ77 to massive data sets, no algorithm to date scales
to inputs that exceed the size of internal memory. In this paper we describe
the first algorithm for computing the LZ77 parsing in external memory. Our
algorithm is fast in practice and will allow the next generation of text
indexes to be realised for massive strings and string collections.Comment: 10 page
Numerical Study of Wave Propagation in Uniaxially Anisotropic Lorentzian Backward Wave Slabs
The propagation and refraction of a cylindrical wave created by a line
current through a slab of backward wave medium, also called left-handed medium,
is numerically studied with FDTD. The slab is assumed to be uniaxially
anisotropic. Several sets of constitutive parameters are considered and
comparisons with theoretical results are made. Electric field distributions are
studied inside and behind the slab. It is found that the shape of the
wavefronts and the regions of real and complex wave vectors are in agreement
with theoretical results.Comment: 6 pages, figure
Low Space External Memory Construction of the Succinct Permuted Longest Common Prefix Array
The longest common prefix (LCP) array is a versatile auxiliary data structure
in indexed string matching. It can be used to speed up searching using the
suffix array (SA) and provides an implicit representation of the topology of an
underlying suffix tree. The LCP array of a string of length can be
represented as an array of length words, or, in the presence of the SA, as
a bit vector of bits plus asymptotically negligible support data
structures. External memory construction algorithms for the LCP array have been
proposed, but those proposed so far have a space requirement of words
(i.e. bits) in external memory. This space requirement is in some
practical cases prohibitively expensive. We present an external memory
algorithm for constructing the bit version of the LCP array which uses
bits of additional space in external memory when given a
(compressed) BWT with alphabet size and a sampled inverse suffix array
at sampling rate . This is often a significant space gain in
practice where is usually much smaller than or even constant. We
also consider the case of computing succinct LCP arrays for circular strings
Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography
We study the feasibility of data based machine learning applied to ultrasound
tomography to estimate water-saturated porous material parameters. In this
work, the data to train the neural networks is simulated by solving wave
propagation in coupled poroviscoelastic-viscoelastic-acoustic media. As the
forward model, we consider a high-order discontinuous Galerkin method while
deep convolutional neural networks are used to solve the parameter estimation
problem. In the numerical experiment, we estimate the material porosity and
tortuosity while the remaining parameters which are of less interest are
successfully marginalized in the neural networks-based inversion. Computational
examples confirms the feasibility and accuracy of this approach
Wave Energy: a Pacific Perspective
This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by The Royal Society and can be found at: http://rsta.royalsocietypublishing.org/.This paper illustrates the status of wave energy development in Pacific Rim countries by characterizing the available resource and introducing the region‟s current and potential future leaders in wave energy converter development. It also describes the existing licensing and permitting process as well as potential environmental concerns. Capabilities of Pacific Ocean testing facilities are described in addition to the region‟s vision of the future of wave energy
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