252,864 research outputs found
On the Minimization of Convex Functionals of Probability Distributions Under Band Constraints
The problem of minimizing convex functionals of probability distributions is
solved under the assumption that the density of every distribution is bounded
from above and below. A system of sufficient and necessary first-order
optimality conditions as well as a bound on the optimality gap of feasible
candidate solutions are derived. Based on these results, two numerical
algorithms are proposed that iteratively solve the system of optimality
conditions on a grid of discrete points. Both algorithms use a block coordinate
descent strategy and terminate once the optimality gap falls below the desired
tolerance. While the first algorithm is conceptually simpler and more
efficient, it is not guaranteed to converge for objective functions that are
not strictly convex. This shortcoming is overcome in the second algorithm,
which uses an additional outer proximal iteration, and, which is proven to
converge under mild assumptions. Two examples are given to demonstrate the
theoretical usefulness of the optimality conditions as well as the high
efficiency and accuracy of the proposed numerical algorithms.Comment: 13 pages, 5 figures, 2 tables, published in the IEEE Transactions on
Signal Processing. In previous versions, the example in Section VI.B
contained some mistakes and inaccuracies, which have been fixed in this
versio
Model-Based Security Testing
Security testing aims at validating software system requirements related to
security properties like confidentiality, integrity, authentication,
authorization, availability, and non-repudiation. Although security testing
techniques are available for many years, there has been little approaches that
allow for specification of test cases at a higher level of abstraction, for
enabling guidance on test identification and specification as well as for
automated test generation.
Model-based security testing (MBST) is a relatively new field and especially
dedicated to the systematic and efficient specification and documentation of
security test objectives, security test cases and test suites, as well as to
their automated or semi-automated generation. In particular, the combination of
security modelling and test generation approaches is still a challenge in
research and of high interest for industrial applications. MBST includes e.g.
security functional testing, model-based fuzzing, risk- and threat-oriented
testing, and the usage of security test patterns. This paper provides a survey
on MBST techniques and the related models as well as samples of new methods and
tools that are under development in the European ITEA2-project DIAMONDS.Comment: In Proceedings MBT 2012, arXiv:1202.582
Why highly expressed proteins evolve slowly
Much recent work has explored molecular and population-genetic constraints on
the rate of protein sequence evolution. The best predictor of evolutionary rate
is expression level, for reasons which have remained unexplained. Here, we
hypothesize that selection to reduce the burden of protein misfolding will
favor protein sequences with increased robustness to translational missense
errors. Pressure for translational robustness increases with expression level
and constrains sequence evolution. Using several sequenced yeast genomes,
global expression and protein abundance data, and sets of paralogs traceable to
an ancient whole-genome duplication in yeast, we rule out several confounding
effects and show that expression level explains roughly half the variation in
Saccharomyces cerevisiae protein evolutionary rates. We examine causes for
expression's dominant role and find that genome-wide tests favor the
translational robustness explanation over existing hypotheses that invoke
constraints on function or translational efficiency. Our results suggest that
proteins evolve at rates largely unrelated to their functions, and can explain
why highly expressed proteins evolve slowly across the tree of life.Comment: 40 pages, 3 figures, with supporting informatio
Robust methods of building regression models : an application to the housing sector.
This article studies robustification strategies for the linear model in the presence of outliers. The advantages of an internal analysis of the robustness of least squares for a given sample are pointed out. The application of this methodology is illustrated by building an explicit model of the determinants of rental housing values in the Madrid Metropolitan Area.Outliers; Influential observations; Robust regression; Cook distance; Hedonic price function; Housing market;
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