On Pseudo-Riemannian Manifolds Whose Ricci Tensor is Parallel

Ricci-parallel Riemannian manifolds have a diagonal Ricci endomorphism Ric and are therefore, at least locally, a product of Einstein manifolds. This fails in the pseudo-Riemannian case. Using, on the one side, a general result in linear algebra due to Klingenberg and on the other side, a theorem on the holonomy of pseudo-Riemannian manifolds, this work classifies the different types of pseudo-Riemannian manifolds whose Ricci tensor is parallel.     

Skew codes of prescribed distance or rank

In this paper we generalize the notion of cyclic code and construct codes as ideals in finite quotients of non-commutative polynomial rings, so called skew polynomial rings of automorphism type. We propose a method to construct block codes of prescribed rank and a method to construct block codes of prescribed distance. Since there is no unique factorization in skew polynomial rings, there are much more ideals and therefore much more codes than in the commutative case. In particular we obtain a [40, 23, 10]₄ code by imposing a distance and a [42,14,21]₈ code by imposing a rank, which both improve by one the minimum distance of the previously best known linear codes of equal length and dimension over those fields. There is a strong connection with linear difference operators and with linearized polynomials (or q-polynomials) reviewed in the first section.      

IndecomposableA-module summands inH * V which are unstable algebras

Letp be a prime and denote byA the modp Steenrod algebra. We determine the indecomposableA-module summands ofH*((ℤ/p)) ^d ;F _p which admit the structure of an unstableA-algebra. In fact, it turns out that this is equivalent to the problem of determining those indecomposableA-module summands which arise as the modp cohomology of a space (or even a classifying space of a finite group). We reduce this problem to one in modular representation theory, namely for whichd andp is the projective cover of the trivial one dimensional GL(d,F _p ) representationF _p a permutation module. Our solution of this latter problem makes use of the classification of subgroups of GL(d,F _p ) acting transitively on (F _p ) ^d \{0} and hence depends on the classification of finite simple groups (on Feit-Thompson's odd order theorem ifp=2).     

A moment inequality of the Marcinkiewicz–Zygmund type for some weakly dependent random fields

The goal of this note is to give a new moment inequality for sums of some weakly dependent random fields. Our result extends moment bounds given by Wu (2007) or Liu and Lin (2009) for causal autoregressive processes and follows by using recursive applications of the Burkhölder inequality for martingales.     

On Morita Equivalence for Simple Generalized Weyl Algebras

We give a necessary condition for Morita equivalence of simple Generalized Weyl algebras of classical type. We propose a reformulation of Hodges’ result, which describes Morita equivalences in case the polynomial defining the Generalized Weyl algebra has degree 2, in terms of isomorphisms of quantum tori, inspired by similar considerations in noncommutative differential geometry. We study how far this link can be generalized for n ≥ 3.     

Structured probabilistic inference

Probabilistic inference is among the main topics with reasoning in uncertainty in AI. For this purpose, Bayesian Networks (BNs) is one of the most successful and efficient Probabilistic Graphical Model (PGM) so far. Since the mid-90s, a growing number of BNs extensions have been proposed. Object-oriented, entity-relationship and first-order logic are the main representation paradigms used to extend BNs. While entity-relationship and first-order models have been successfully used for machine learning in defining lifted probabilistic inference, object-oriented models have been mostly underused. Structured inference, which exploits the structural knowledge encoded in an object-oriented PGM, is a surprisingly unstudied technique. In this paper we propose a full object-oriented framework for PRM and propose two extensions of the state-of-the-art structured inference algorithm: SPI which removes the major flaws of existing algorithms and SPISBB which largely enhances SPI by using d-separation.     

Einstein-Weyl structures on lightlike hypersurfaces

We study Weyl structures on lightlike hypersurfaces endowed with a conformal structure of certain type and specific screen distribution: the Weyl screen structures. We investigate various differential geometric properties of Einstein-Weyl screen structures on lightlike hypersurfaces and show that, for ambient Lorentzian space ? ₁ ⁿ⁺² and a totally umbilical screen foliation, there is a strong interplay with the induced (Riemannian) Weyl-structure on the leaves.     

A spatial scan statistic for case event data based on connected components

We propose a new spatial scan statistic based on graph theory as a method for detecting irregularly-shaped clusters of events over space. A graph-based method is proposed for identifying potential clusters in spatial point processes. It relies on linking the events closest than a given distance and thus defining a graph associated to the point process. The set of possible clusters is then restricted to windows including the connected components of the graph. The concentration in each of these possible clusters is measured through classical concentration indices based on likelihood ratio and also through a new concentration index which does not depend on any alternative hypothesis. These graph-based spatial scan tests seem to be very powerful against any arbitrarily-shaped cluster alternative, whatever the dimension of the data. These results have applications in various fields, such as the epidemiological study of rare diseases or the analysis of astrophysical data.     

Solving a robotic assembly line balancing problem using efficient hybrid methods

In this paper we are studying a robotic assembly line balancing problem. The goal is to maximize the efficiency of the line and to balance the different tasks between the robots by defining the suitable tasks and components to assign to each robot. We are interested in a robotic line which consists of seizing the products on a moving conveyor and placing them on different location points. The performances evaluations of the system are done using a discret event simulation model. This latter has been developed with C++ language. As in our industrial application we are bounded by the execution time, we propose some resolution methods which define the suitable component and point positions in order to define the strategy of pick and place for each robot. These methods are based on the ant colony optimization, particle swarm optimization and genetic algorithms. To enhance the quality of the developed algorithms and to avoid local optima, we have coupled these algorithms with guided local search. After that, an exact method based on full enumeration is also developed to assess the quality of the developed methods. Then, we try to select the best algorithm which is able to get the best solutions with a small execution time. This is the main advantage of our methods compared to exact methods. This fact represents a great interest taking in consideration that the selected methods are used to manage the functioning of real industrial robotic assembly lines. Numerical results show that the selected algorithm performs optimally for the tested instances in a reasonable computation time and satisfies the industrial constraint.