40,485 research outputs found
Weights of Markov Traces on Hecke algebras
We compute the weights, i.e. the values at the minimal idempotents, for the
Markov trace on the Hecke algebra of type and type . In order to prove
the weight formula, we define representations of the Hecke algebra of type
onto a reduced Hecke algebre of type . To compute the weights for type
we use the inclusion of the Hecke algebra of type into the Hecke algebra of
type .Comment: 23 pages. see also http://math.ucsd.edu/~rorellan
The Hopf algebra of uniform block permutations. Extended abstract
We introduce the Hopf algebra of uniform block permutations and show that it
is self-dual, free, and cofree. These results are closely related to the fact
that uniform block permutations form a factorizable inverse monoid. This Hopf
algebra contains the Hopf algebra of permutations of Malvenuto and Reutenauer
and the Hopf algebra of symmetric functions in non-commuting variables of
Gebhard, Rosas, and Sagan.Comment: Extended abstrac
Complete Monotonicity of Fractional Kinetic Functions
The introduction of a fractional differential operator defined in terms of
the Riemann-Liouville derivative makes it possible to generalize the kinetic
equations used to model relaxation in dielectrics. In this context such
fractional equations are called fractional kinetic relaxation equations and
their solutions, called fractional kinetic relaxation functions, are given in
terms of Mittag-Leffler functions. These fractional kinetic relaxation
functions generalize the kinetic relaxation functions associated with the
Debye, Cole-Cole, Cole-Davidson and Havriliak-Negami models, as the latter
functions become particular cases of the fractional solutions, obtained for
specific values of the parameter specifying the order of the derivative. The
aim of this work is to analyse the behavior of these fractional functions in
the time variable. As theoretical tools we use the theorem by Bernstein on the
complete monotonicity of functions together with Titchmarsh's inversion
formula. The last part of the paper contains the graphics of some of those
functions, obtained by varying the value of the parameter in the fractional
differential operator and in the corresponding Mittag-Leffler functions. The
graphics were made with Mathematica 10.4.Comment: 28 pages, 38 figure
A micro-structured continuum modelling compacting fluid-saturated grounds: the effects of pore-size scale parameter
The effect of a "pore-size" length-scale parameter l on compaction of grounds
with fluid inclusions is studied. They are modelled as continua endowed with
micro-structure by means of the macro-modelling procedure proposed in [2]. We
show the dependence of field evolution equations on the micro-structure
parameter l and compare our model with the homogenized asymptotic ones. The
consideration of the pore size 1 allows us to forecast the onset of
micro-displacement waves as a consequence of a ground settling and to suggest a
possible description of the genesis of certain microearthquakes [5] [6].Comment: 18 page
Nonparametric estimation of a regression function using the gamma kernel method in ergodic processes
In this paper we consider the nonparametric estimation of density and
regression functions with non-negative support using a gamma kernel procedure
introduced by Chen (2000). Strong uniform consistency and asymptotic normality
of the corresponding estimators are established under a general ergodic
assumption on the data generation process. Our results generalize those of Shi
and Song (2016), obtained in the classic i.i.d. framework, and the works of
Bouezmarni and Rombouts (2008, 2010b) and Gospodinov and Hirukawa (2007) for
mixing time series.Comment: 29 page
Using Dissortative Mating Genetic Algorithms to Track the Extrema of Dynamic Deceptive Functions
Traditional Genetic Algorithms (GAs) mating schemes select individuals for
crossover independently of their genotypic or phenotypic similarities. In
Nature, this behaviour is known as random mating. However, non-random schemes -
in which individuals mate according to their kinship or likeness - are more
common in natural systems. Previous studies indicate that, when applied to GAs,
negative assortative mating (a specific type of non-random mating, also known
as dissortative mating) may improve their performance (on both speed and
reliability) in a wide range of problems. Dissortative mating maintains the
genetic diversity at a higher level during the run, and that fact is frequently
observed as an explanation for dissortative GAs ability to escape local optima
traps. Dynamic problems, due to their specificities, demand special care when
tuning a GA, because diversity plays an even more crucial role than it does
when tackling static ones. This paper investigates the behaviour of
dissortative mating GAs, namely the recently proposed Adaptive Dissortative
Mating GA (ADMGA), on dynamic trap functions. ADMGA selects parents according
to their Hamming distance, via a self-adjustable threshold value. The method,
by keeping population diversity during the run, provides an effective means to
deal with dynamic problems. Tests conducted with deceptive and nearly deceptive
trap functions indicate that ADMGA is able to outperform other GAs, some
specifically designed for tracking moving extrema, on a wide range of tests,
being particularly effective when speed of change is not very fast. When
comparing the algorithm to a previously proposed dissortative GA, results show
that performance is equivalent on the majority of the experiments, but ADMGA
performs better when solving the hardest instances of the test set.Comment: Technical report complementing Carlos Fernandes' Ph
Self-Regulated Artificial Ant Colonies on Digital Image Habitats
Artificial life models, swarm intelligent and evolutionary computation
algorithms are usually built on fixed size populations. Some studies indicate
however that varying the population size can increase the adaptability of these
systems and their capability to react to changing environments. In this paper
we present an extended model of an artificial ant colony system designed to
evolve on digital image habitats. We will show that the present swarm can adapt
the size of the population according to the type of image on which it is
evolving and reacting faster to changing images, thus converging more rapidly
to the new desired regions, regulating the number of his image foraging agents.
Finally, we will show evidences that the model can be associated with the
Mathematical Morphology Watershed algorithm to improve the segmentation of
digital grey-scale images. KEYWORDS: Swarm Intelligence, Perception and Image
Processing, Pattern Recognition, Mathematical Morphology, Social Cognitive
Maps, Social Foraging, Self-Organization, Distributed Search.Comment: 8 pages, 17 figures, full pictures in
http://alfa.ist.utl.pt/~cvrm/staff/vramos/Vramos-WCLC05b.pd
Detecting topological sectors in continuum Yang-Mills theory and the fate of BRST symmetry
In this work, motivated by Laplacian type center gauges in the lattice,
designed to avoid the Gribov problem, we introduce a new family of gauge
fixings for pure Yang-Mills theories in the continuum. This procedure separates
the partition function into partial contributions associated with different
sectors, containing center vortices and correlated monopoles. We show that, on
each sector, the gauge fixed path-integral displays a BRST symmetry, however,
it cannot be globally extended due to sector dependent boundary conditions on
the ghost fields. These are nice features as they would permit to discuss the
independence of the partial contributions on gauge parameters,, while opening a
window for the space of quantum states to be different from the perturbative
one, which would be implied if topological configurations were removed.Comment: 7 pages, REVTe
On Self-Regulated Swarms, Societal Memory, Speed and Dynamics
We propose a Self-Regulated Swarm (SRS) algorithm which hybridizes the
advantageous characteristics of Swarm Intelligence as the emergence of a
societal environmental memory or cognitive map via collective pheromone laying
in the landscape (properly balancing the exploration/exploitation nature of our
dynamic search strategy), with a simple Evolutionary mechanism that trough a
direct reproduction procedure linked to local environmental features is able to
self-regulate the above exploratory swarm population, speeding it up globally.
In order to test his adaptive response and robustness, we have recurred to
different dynamic multimodal complex functions as well as to Dynamic
Optimization Control problems, measuring reaction speeds and performance. Final
comparisons were made with standard Genetic Algorithms (GAs), Bacterial
Foraging strategies (BFOA), as well as with recent Co-Evolutionary approaches.
SRS's were able to demonstrate quick adaptive responses, while outperforming
the results obtained by the other approaches. Additionally, some successful
behaviors were found. One of the most interesting illustrate that the present
SRS collective swarm of bio-inspired ant-like agents is able to track about 65%
of moving peaks traveling up to ten times faster than the velocity of a single
individual composing that precise swarm tracking system.Comment: 11 pages, 8 figures,
http://alfa.ist.utl.pt/~cvrm/staff/vramos/refs_2005.html, KEYWORDS: Dynamic
Optimization, Dynamic Optimal Control problems, Swarm Intelligence,
Self-Organization, Societal Implicit Memory. Submitted to ALIFE-X, Int. Conf.
on the Simulation and Synthesis of Living Systems, Bloomington, Indiana, USA,
June 3-7, 200
SimOutUtils - Utilities for analyzing time series simulation output
SimOutUtils is a suite of MATLAB/Octave functions for studying and analyzing
time series-like output from stochastic simulation models. More specifically,
SimOutUtils allows modelers to study and visualize simulation output dynamics,
perform distributional analysis of output statistical summaries, as well as
compare these summaries in order to assert the statistical equivalence of two
or more model implementations. Additionally, the provided functions are able to
produce publication quality figures and tables showcasing results from the
specified simulation output studies.Comment: The peer-reviewed version of this paper is published in the Journal
of Open Research Software at http://doi.org/10.5334/jors.110 . This version
is typeset by the authors and differs only in pagination and typographical
detai
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