Object-oriented
parallel software for radio wave propagation simulation in urban environment
F.
Guidec, P. Calégari, P. Kuonen, M. Pahud
Abstract.
The
objective of the European project STORMS (Software Tools for the Optimization of
Resources in Mobile Systems) is to develop a software tool to be used for design
and planning of the future Universal Mobile Telecommunication System (UMTS). In
this context the ParFlow method permits the simulation of outdoor radio wave
propagation in urban environment, modeling the physical system in terms of the
motion of fictitious microscopic particles over a lattice. This paper gives an
overview of the Parflow method, and reports the design, the implementation, and
the performance analysis of ParFlow++, an object-oriented irregular parallel
software for urban outdoor radio wave propagation prediction.
A
morphological approach to Hough transform on an instruction systolic array
B.
Schmidt, M. Schimmler, H. Schröder
Abstract.
Instruction systolic arrays have been developed in order to combine the speed
and the simplicity of systolic arrays with the flexibility of MIMD parallel
computer systems. Instruction systolic arrays are available as quadratic arrays
of small RISC processors capable of performing integer and floating point
arithmetic. In this paper a new algorithm for line detection is presented which
applies the morphological approach to the well-known Hough transform. The
quality of its results is significantly higher than that of the classical Hough
transform. Our algorithm has an AT-complexity
of O(N3). This matches the
one of the best known alternatives in the literature. It will be shown that the
new algorithm is more efficient in practical applications. It has been tailored
towards the capabilities of the instruction systolic array. This leads to a
high-speed implementation on Systola 1024, the first low cost parallel computer
of this particular architecture on the market.
Nonspecificity
degrees of basic probability assignments in dempster-shafer theory
I.
Kramosil
Abstract.
Basic probability assignment is a probability distribution on the power-set
(set of all subsets) of a finite set S
and the nonspecificity degree of this basic probability assignment is the
normalized expected value of the size (cardinality) of subsets of S
with respect to this probability distribution. This notion enables to express
formally and to prove the intuitive feelings of improving one's basic
probability assignment and belief function when combining it with another one by
the Dempster combination rule. It enables also to define a basic probability
assignment which can be used, at least in certain relations, as an inverse basic
probability assignment to the given one with respect to Dempster rule, even if
we know that such an inverse element cannot be defined up to the most trivial
case of the vacuous basic probability assignment. Analogous properties of the
combination rule dual to the Dempster rule are also briefly investigated.
A
computational model of evolution: Haploidy versus diploidy
P.
Isasi, A. Sanchis, J. Molina, A. Berlanda
Abstract.
In this paper, the study of diploidy is introduced like and important mechanism
for memory reinforcement in artificial environments where adaptation is very
important. The individuals of this ecosystem are able to genetically
"learn" the best behaviour for survival. Critical changes, happening
in the environmental conditions, require the presence of diploidy to ensure the
survival of species. By means of new gene-dominance configurations, a way to
shield the individuals from erroneous selection is provided. These two concepts
appear like important elements for artificial systems which have to evolve in
environments with some degree of instability.
Possibilistic
information measures and selection approach
Do
Van Thanh
Abstract.
The aim of this paper is to introduce a use of both the principle of minimal
specificity (mS) and maximal buoyancy (MB) for selecting a distribution from a
given set of quantitative possibility distributions. In this paper some
conditions of a set of possibility distributions and weights which guarantee
"always selected situation" of a possibility distribution selected by
the use of these principles from the given distribution set are proposed.