43,199 research outputs found
A Simple Proof of the Alternation Theorem
A simple proof of the alternation theorem for minimax FIR filter design is presented in this paper. It requires no background on mathematical optimization theory, and is based on easily understood properties of filters with equiripple behavior. The method is similar to the classical counting argument used in early mathematics literature. The contribution here is a simplified presentation which directly uses filter design language
An isogeometric analysis for elliptic homogenization problems
A novel and efficient approach which is based on the framework of
isogeometric analysis for elliptic homogenization problems is proposed. These
problems possess highly oscillating coefficients leading to extremely high
computational expenses while using traditional finite element methods. The
isogeometric analysis heterogeneous multiscale method (IGA-HMM) investigated in
this paper is regarded as an alternative approach to the standard Finite
Element Heterogeneous Multiscale Method (FE-HMM) which is currently an
effective framework to solve these problems. The method utilizes non-uniform
rational B-splines (NURBS) in both macro and micro levels instead of standard
Lagrange basis. Beside the ability to describe exactly the geometry, it
tremendously facilitates high-order macroscopic/microscopic discretizations
thanks to the flexibility of refinement and degree elevation with an arbitrary
continuity level provided by NURBS basis functions. A priori error estimates of
the discretization error coming from macro and micro meshes and optimal micro
refinement strategies for macro/micro NURBS basis functions of arbitrary orders
are derived. Numerical results show the excellent performance of the proposed
method
A new root-knot nematode, Meloidogyne moensi n. sp. (Nematoda : Meloidogynidae), parasitizing Robusta coffee from Western Highlands, Vietnam
A new root-knot nematode, parasitizing Robusta coffee in Dak Lak Province, Western Highlands of Vietnam, is described as Meloidogyne moensi n. sp. Morphological and molecular analyses demonstrated that this species differs clearly from other previously described root-knot nematodes. Morphologically, the new species is characterized by a swollen body of females with a small posterior protuberance that elongated from ovoid to saccate; perineal patterns with smooth striae, continuous and low dorsal arch; lateral lines marked as a faint space or linear depression at junction of the dorsal and ventral striate; distinct phasmids; perivulval region free of striae; visible and wide tail terminus surrounding by concentric circles of striae; medial lips of females in dumbbell-shaped and slightly raised above lateral lips; female stylet is normally straight with posteriorly sloping stylet knobs; lip region of second stage juvenile (J2) is not annulated; medial lips and labial disc of J2 formed dumbbell shape; lateral lips are large and triangular; tail of J2 is conoid with rounded unstriated tail tip; distinct phasmids and hyaline; dilated rectum. Meloidogyne moensi n. sp. is most similar to M. africana, M. ottersoni by prominent posterior protuberance. Results of molecular analysis of rDNA sequences including the D2-D3 expansion regions of 28S rDNA, COI, and partial COII/16S rRNA of mitochondrial DNA support for the new species status
MDFEM: Multivariate decomposition finite element method for elliptic PDEs with lognormal diffusion coefficients using higher-order QMC and FEM
We introduce the multivariate decomposition finite element method for
elliptic PDEs with lognormal diffusion coefficient where is a
Gaussian random field defined by an infinite series expansion
with and a given sequence of functions . We
use the MDFEM to approximate the expected value of a linear functional of the
solution of the PDE which is an infinite-dimensional integral over the
parameter space. The proposed algorithm uses the multivariate decomposition
method to compute the infinite-dimensional integral by a decomposition into
finite-dimensional integrals, which we resolve using quasi-Monte Carlo methods,
and for which we use the finite element method to solve different instances of
the PDE.
We develop higher-order quasi-Monte Carlo rules for integration over the
finite-dimensional Euclidean space with respect to the Gaussian distribution by
use of a truncation strategy. By linear transformations of interlaced
polynomial lattice rules from the unit cube to a multivariate box of the
Euclidean space we achieve higher-order convergence rates for functions
belonging to a class of anchored Gaussian Sobolev spaces while taking into
account the truncation error.
Under appropriate conditions, the MDFEM achieves higher-order convergence
rates in term of error versus cost, i.e., to achieve an accuracy of
the computational cost is where and
are respectively the cost of the quasi-Monte Carlo
cubature and the finite element approximations, with
for some and the physical dimension, and is a parameter representing the sparsity of .Comment: 48 page
Outward Influence and Cascade Size Estimation in Billion-scale Networks
Estimating cascade size and nodes' influence is a fundamental task in social,
technological, and biological networks. Yet this task is extremely challenging
due to the sheer size and the structural heterogeneity of networks. We
investigate a new influence measure, termed outward influence (OI), defined as
the (expected) number of nodes that a subset of nodes will activate,
excluding the nodes in S. Thus, OI equals, the de facto standard measure,
influence spread of S minus |S|. OI is not only more informative for nodes with
small influence, but also, critical in designing new effective sampling and
statistical estimation methods.
Based on OI, we propose SIEA/SOIEA, novel methods to estimate influence
spread/outward influence at scale and with rigorous theoretical guarantees. The
proposed methods are built on two novel components 1) IICP an important
sampling method for outward influence, and 2) RSA, a robust mean estimation
method that minimize the number of samples through analyzing variance and range
of random variables. Compared to the state-of-the art for influence estimation,
SIEA is times faster in theory and up to several orders of
magnitude faster in practice. For the first time, influence of nodes in the
networks of billions of edges can be estimated with high accuracy within a few
minutes. Our comprehensive experiments on real-world networks also give
evidence against the popular practice of using a fixed number, e.g. 10K or 20K,
of samples to compute the "ground truth" for influence spread.Comment: 16 pages, SIGMETRICS 201
Importance Sketching of Influence Dynamics in Billion-scale Networks
The blooming availability of traces for social, biological, and communication
networks opens up unprecedented opportunities in analyzing diffusion processes
in networks. However, the sheer sizes of the nowadays networks raise serious
challenges in computational efficiency and scalability.
In this paper, we propose a new hyper-graph sketching framework for inflence
dynamics in networks. The central of our sketching framework, called SKIS, is
an efficient importance sampling algorithm that returns only non-singular
reverse cascades in the network. Comparing to previously developed sketches
like RIS and SKIM, our sketch significantly enhances estimation quality while
substantially reducing processing time and memory-footprint. Further, we
present general strategies of using SKIS to enhance existing algorithms for
influence estimation and influence maximization which are motivated by
practical applications like viral marketing. Using SKIS, we design high-quality
influence oracle for seed sets with average estimation error up to 10x times
smaller than those using RIS and 6x times smaller than SKIM. In addition, our
influence maximization using SKIS substantially improves the quality of
solutions for greedy algorithms. It achieves up to 10x times speed-up and 4x
memory reduction for the fastest RIS-based DSSA algorithm, while maintaining
the same theoretical guarantees.Comment: 12 pages, to appear in ICDM 2017 as a regular pape
Relationship Between Obesity and Periodontal Status in Vietnamese Patients
This study aims to investigate periodontal status, and the relationship between obesity and periodontal status in patients who first visited the Institute of Traditional Medicine, Ho Chi Minh City, Vietnam. 118 patients aged 18 or older, including 56 obese subjects (BMI≥27.5, mean age: 33.8, males: 11, females: 45) and 62 non-obese subjects (BMI<27.5, mean age: 34.3, males: 4, females: 58) were enrolled for a period of 5 months from February 2014 to June 2014. The information on socio-demographic characteristics and dental habits were collected by questionnaire. Periodontal status (PLI, GI, BOP, PD, CAL) was examined and the anthropometric index was measured. There was significantly higher prevalence of periodontitis (39.3%) in the obese group than the non-obese group (16.4%). Means of GI, BOP, PD, and CAL in obese subjects were significantly higher than those in non-obese subjects. Significantly higher percentages of subjects who had lower education, visited dental offices, scaled and polished their teeth regularly were in the non-obese group than in the obese group. Multiple logistic regression analysis revealed that age (OR=3.10), routine of dental visit (OR=3.34) and obesity (OR=2.79) were risk factors significantly related to periodontitis. Periodontal status in obese subjects was poorer than non-obese subjects. Obesity might be the risk factor for periodontitis in Vietnamese patients
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