Sandrine Vial

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Indexing moving objects (MO) is a hot topic in the field of moving objects databases since many years. An impressive number of access methods have been proposed to optimize the processing of MO-related queries. Several methods have focused on spatio-temporal range queries, which represent the foundation of MO trajectory queries. Surprisingly, only a few of(More)
We present an algorithm for automatically predicting the topological family of any RNA three-way junction, given only the information from the secondary structure: the sequence and the Watson-Crick pairings. The parameters of the algorithm have been determined on a data set of 33 three-way junctions whose 3D conformation is known. We applied the algorithm(More)
In this paper we describe routing functions for optical packets in point-to-point networks. These functions are based on Eulerian tours. We first define different measures to handle the efficiency of this routing. Then, we describe an algorithm to compute these measures. Moreover, we present such an Eulerian routing in the Square Mesh and we prove that the(More)
Broadcasting (one-to-all) and gossiping (all-to-all) are two major communication paradigms that were considered from both practical and theoretical points of view. Indeed, such communication patterns frequently appear in parallel programming, and therefore are included in most of the communication libraries (e.g., MPI or PVM). Also, broadcasting and(More)
In this paper we propose PARINET, a new access method to efficiently retrieve the trajectories of objects moving in networks. The structure of PARINET is based on a combination of graph partitioning and a set of composite B<sup>+</sup>-tree local indexes. PARINET is designed for historical data and relies on the distribution of the data over the network as(More)
Graph searching is one of the most popular tool for analyzing the chase for a powerful and hostile software agent (called the ”intruder”), by a set of software agents (called the ”searchers”) in a network. The existing solutions for the graph searching problem suffer however from a serious drawback: they are mostly centralized and assume a global(More)
We present a new approach for the prediction of the coarse-grain 3D structure of RNA molecules. We model a molecule as being made of helices and junctions. Those junctions are classified into topological families that determine their preferred 3D shapes. All the parts of the molecule are then allowed to establish long-distance contacts that induce a 3D(More)