An extension of the Ruzsa-Szemerédi theorem

We let G (r) (n,m) denotethesetofr-uniform hypergraphs with n vertices and m edges, and f (r) (n,p,s) is the smallest m such that every member of G (r) (n,m) containsamember of G (r) (p,s). In this paper we are interested in fixed values r, p and s for which f (r) (n,p,s) grows quadratically with n. A probabilistic construction of Brown, Erdős and T. Sós ([2]) implies that f (r) (n,s(r − 2) + 2,s)=Ω(n 2). In the other direction the most interesting question they could not settle was whether f (3) (n,6,3) = o(n 2). This was proved by Ruzsa and Szemerédi [11]. Then Erdős,FranklandRödl [6] extended this result to any r: f (r) (n,3(r − 2) + 3,3) = o(n 2), and they conjectured ([4], [6]) that the Brown, Erdős and T. Sós bound is best possible in the sense that f (r) (n,s(r −2)+ 3,s)=o(n 2). In this paper by giving an extension of the Erdős, Frankl, Rödl Theorem (and thus the Ruzsa–Szemerédi Theorem) we show that indeed the Brown, Erdős, T. Sós Theorem is not far from being best possible. Our main result is f (r) (n, s(r − 2) + 2 + ⌊log 2 s⌋,s)=o(n 2). 1

The effect of elevated temperature exposure on the fracture toughness of solid wood and structural wood composites

This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Springer and can be found at: http://www.springer.com/life+sciences/forestry/journal/226.Fracture toughness of wood and wood composites has traditionally been characterized by a stress intensity factor, an initiation strain energy release rate (G[subscript init]) or a total energy to fracture (G[subscript f]). These parameters provide incomplete fracture characterization for these materials because the toughness changes as the crack propagates. Thus for materials such as wood, oriented strand board (OSB), plywood and laminated veneer lumber (LVL), it is essential to characterize the fracture properties during crack propagation by measuring a full crack resistant or R curve. This study used energy methods during crack propagation to measure full R curves and then compared the fracture properties of wood and various wood-based composites such as, OSB, LVL and plywood. The effect of exposure to elevated temperature on fracture properties of these materials was also studied. The steady state energy release rate (G[subscript SS]) of wood was lower than that of wood composites such as LVL, plywood and OSB. The resin in wood composites provides them with a higher fracture toughness compared to solid lumber. Depending upon the internal structure of the material the mode of failure also varied. With exposure to elevated temperatures, G[subscript SS] for all materials decreased while the failure mode remained the same. The scatter associated with conventional bond strength tests, such as internal bond (IB) and bond classification tests, renders any statistical comparison using those tests difficult. In contrast, fracture tests with R curve analysis may provide an improved tool for characterization of bond quality in wood composites

Intelligent Self-Repairable Web Wrappers

The amount of information available on the Web grows at an incredible high rate. Systems and procedures devised to extract these data from Web sources already exist, and different approaches and techniques have been investigated during the last years. On the one hand, reliable solutions should provide robust algorithms of Web data mining which could automatically face possible malfunctioning or failures. On the other, in literature there is a lack of solutions about the maintenance of these systems. Procedures that extract Web data may be strictly interconnected with the structure of the data source itself; thus, malfunctioning or acquisition of corrupted data could be caused, for example, by structural modifications of data sources brought by their owners. Nowadays, verification of data integrity and maintenance are mostly manually managed, in order to ensure that these systems work correctly and reliably. In this paper we propose a novel approach to create procedures able to extract data from Web sources -- the so called Web wrappers -- which can face possible malfunctioning caused by modifications of the structure of the data source, and can automatically repair themselves.\u

Learning Stochastic Tree Edit Distance

pages 42-53International audienceTrees provide a suited structural representation to deal with complex tasks such as web information extraction, RNA secondary structure prediction, or conversion of tree structured documents. In this context, many applications require the calculation of similarities between tree pairs. The most studied distance is likely the tree edit distance for which improvements in terms of complexity have been achieved during the last decade. However, this classic edit distance usually uses a priori fixed edit costs which are often difficult to tune, that leaves little room for tackling complex problems. In this paper, we focus on the learning of a stochastic tree edit distance. We use an adaptation of the expectation-maximization algorithm for learning the primitive edit costs. We carried out several series of experiments that confirm the interest to learn a tree edit distance rather than a priori imposing edit costs

Melody recognition with learned edit distances

In a music recognition task, the classification of a new melody is often achieved by looking for the closest piece in a set of already known prototypes. The definition of a relevant similarity measure becomes then a crucial point. So far, the edit distance approach with a-priori fixed operation costs has been one of the most used to accomplish the task. In this paper, the application of a probabilistic learning model to both string and tree edit distances is proposed and is compared to a genetic algorithm cost fitting approach. The results show that both learning models outperform fixed-costs systems, and that the probabilistic approach is able to describe consistently the underlying melodic similarity model.This work was funded by the French ANR Marmota project, the Spanish PROSEMUS project (TIN2006-14932-C02), the research programme Consolider Ingenio 2010 (MIPRCV, CSD2007-00018), and the Pascal Network of Excellence