700 research outputs found
Multigrid solver for axisymmetrical 2D fluid equations
We have developed an efficient algorithm for steady axisymmetrical 2D fluid
equations. The algorithm employs multigrid method as well as standard implicit
discretization schemes for systems of partial differential equations. Linearity
of the multigrid method with respect to the number of grid points allowed us to
use grid, where we could achieve solutions in several minutes.
Time limitations due to nonlinearity of the system are partially avoided by
using multi level grids(the initial solution on grid was
extrapolated steady solution from grid which allowed using
"long" integration time steps). The fluid solver may be used as the basis for
hybrid codes for DC discharges.Comment: preliminary version; presented at 28 ICPIG, July 15-20, 2007, Prague,
Czech Republi
Perioperative infection prophylaxis and risk factor impact in colon surgery
Background: A prospective observational study was undertaken in 2,481 patients undergoing elective colon resection in 114 German centers to identify optimal drug and dosing modalities and risk factors for postoperative infection. Methods: Patients were pair matched using six risk factors and divided into 672 pairs (ceftriaxone vs, other cephalosporins, group A) and 400 pairs (ceftriaxone vs. penicillins, group B). End points were local and systemic postoperative infection and cost effectiveness. Results: Local infection rates were 6.0 versus 6.5% (group A) and 4.0 versus 10.5% (group B); systemic infection rates in groups A and B were 4.9 versus 6.3% and 3.3 versus 10.5%, respectively. Ceftriaxone was more effective than penicillins overall (6.8 vs. 17.8%, p < 0.001). Length of postoperative hospital stay was 16.2 versus 16.9 days (group A) and 15.8 versus 17.6 days (group B). Of the six risk factors, age and concomitant disease were significant for systemic infection, and blood loss, rectum resection and immunosuppressive therapy were significant for local infection. Penicillin was a risk factor compared to ceftriaxone (p < 0.0001). Ceftriaxone saved Q160.7 versus other cephalosporins and O416.2 versus penicillins. Conclusion: Clinical and microbiological efficacy are responsible for the cost effectiveness of ceftriaxone for perioperative prophylaxis in colorectal surgery. Copyright (C) 2000 S. Karger AG, Basel
Identification of clusters of companies in stock indices via Potts super-paramagnetic transitions
The clustering of companies within a specific stock market index is studied
by means of super-paramagnetic transitions of an appropriate q-state Potts
model where the spins correspond to companies and the interactions are
functions of the correlation coefficients determined from the time dependence
of the companies' individual stock prices. The method is a generalization of
the clustering algorithm by Domany et. al. to the case of anti-ferromagnetic
interactions corresponding to anti-correlations. For the Dow Jones Industrial
Average where no anti-correlations were observed in the investigated time
period, the previous results obtained by different tools were well reproduced.
For the Standard & Poor's 500, where anti-correlations occur, repulsion between
stocks modify the cluster structure.Comment: 4 pages; changed conten
ON THE DEVELOPMENT OF A DATASET PUBLICATION GUIDELINE: DATA REPOSITORIES AND KEYWORD ANALYSIS IN ISPRS DOMAIN
The FAIR principle (find, access, interoperability, reuse) forms a sustainable resource for scientific exchange between researchers. Currently, the implementation of this principle is an important process for future research projects. To support this process in the ISPRS community, the usage of data repositories for dataset publication has the potential to bring closer the achievement of the FAIR principle. Therefore, we (1) analysed available data repositories, (2) identified common keywords in ISPRS publications and (3) developed a tool for searching appropriate repositories. Thus, infrastructures from the field of geosciences, that can already be used, become more accessible
CURRENT STATUS OF THE BENCHMARK DATABASE BEMEDA
Open science is an important attribute for developing new approaches. Especially, the data component plays a significant role. The FAIR principle provides a good orientation towards open data. One part of FAIR is findability. Thus, domain specific dataset search platforms were developed: the Earth Observation Database and our Benchmark Metadata Database (BeMeDa). In addition to the search itself, the datasets found by this platforms can be compared with each other with regard to their interoperability. We compare these two platforms and present an update of our platform BeMeDa. This update includes additional location information about the datasets and a new frontend design with improved usability. We rely on user feedback for further improvements and enhancements
On SAT representations of XOR constraints
We study the representation of systems S of linear equations over the
two-element field (aka xor- or parity-constraints) via conjunctive normal forms
F (boolean clause-sets). First we consider the problem of finding an
"arc-consistent" representation ("AC"), meaning that unit-clause propagation
will fix all forced assignments for all possible instantiations of the
xor-variables. Our main negative result is that there is no polysize
AC-representation in general. On the positive side we show that finding such an
AC-representation is fixed-parameter tractable (fpt) in the number of
equations. Then we turn to a stronger criterion of representation, namely
propagation completeness ("PC") --- while AC only covers the variables of S,
now all the variables in F (the variables in S plus auxiliary variables) are
considered for PC. We show that the standard translation actually yields a PC
representation for one equation, but fails so for two equations (in fact
arbitrarily badly). We show that with a more intelligent translation we can
also easily compute a translation to PC for two equations. We conjecture that
computing a representation in PC is fpt in the number of equations.Comment: 39 pages; 2nd v. improved handling of acyclic systems, free-standing
proof of the transformation from AC-representations to monotone circuits,
improved wording and literature review; 3rd v. updated literature,
strengthened treatment of monotonisation, improved discussions; 4th v. update
of literature, discussions and formulations, more details and examples;
conference v. to appear LATA 201
Cost functions for pairwise data clustering
Cost functions for non-hierarchical pairwise clustering are introduced, in
the probabilistic autoencoder framework, by the request of maximal average
similarity between the input and the output of the autoencoder. The partition
provided by these cost functions identifies clusters with dense connected
regions in data space; differences and similarities with respect to a well
known cost function for pairwise clustering are outlined.Comment: 5 pages, 4 figure
Preferencial growth: exact solution of the time dependent distributions
We consider a preferential growth model where particles are added one by one
to the system consisting of clusters of particles. A new particle can either
form a new cluster (with probability q) or join an already existing cluster
with a probability proportional to the size thereof. We calculate exactly the
probability \Pm_i(k,t) that the size of the i-th cluster at time t is k. We
analyze the asymptotics, the scaling properties of the size distribution and of
the mean size as well as the relation of our system to recent network models.Comment: 8 pages, 4 figure
Macrostate Data Clustering
We develop an effective nonhierarchical data clustering method using an
analogy to the dynamic coarse graining of a stochastic system. Analyzing the
eigensystem of an interitem transition matrix identifies fuzzy clusters
corresponding to the metastable macroscopic states (macrostates) of a diffusive
system. A "minimum uncertainty criterion" determines the linear transformation
from eigenvectors to cluster-defining window functions. Eigenspectrum gap and
cluster certainty conditions identify the proper number of clusters. The
physically motivated fuzzy representation and associated uncertainty analysis
distinguishes macrostate clustering from spectral partitioning methods.
Macrostate data clustering solves a variety of test cases that challenge other
methods.Comment: keywords: cluster analysis, clustering, pattern recognition, spectral
graph theory, dynamic eigenvectors, machine learning, macrostates,
classificatio
Data clustering and noise undressing for correlation matrices
We discuss a new approach to data clustering. We find that maximum likelihood
leads naturally to an Hamiltonian of Potts variables which depends on the
correlation matrix and whose low temperature behavior describes the correlation
structure of the data. For random, uncorrelated data sets no correlation
structure emerges. On the other hand for data sets with a built-in cluster
structure, the method is able to detect and recover efficiently that structure.
Finally we apply the method to financial time series, where the low temperature
behavior reveals a non trivial clustering.Comment: 8 pages, 5 figures, completely rewritten and enlarged version of
cond-mat/0003241. Submitted to Phys. Rev.
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