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

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

A distance for partially labeled trees

In a number of practical situations, data have structure and the relations among its component parts need to be coded with suitable data models. Trees are usually utilized for representing data for which hierarchical relations can be defined. This is the case in a number of fields like image analysis, natural language processing, protein structure, or music retrieval, to name a few. In those cases, procedures for comparing trees are very relevant. An approximate tree edit distance algorithm has been introduced for working with trees labeled only at the leaves. In this paper, it has been applied to handwritten character recognition, providing accuracies comparable to those by the most comprehensive search method, being as efficient as the fastest.This work is supported by the Spanish Ministry projects DRIMS (TIN2009-14247-C02), and Consolider Ingenio 2010 (MIPRCV, CSD2007-00018), partially supported by EU ERDF and the Pascal Network of Excellence

New partially labelled tree similarity measure: a case study

Trees are a powerful data structure for representing data for which hierarchical relations can be defined. They have been applied in a number of fields like image analysis, natural language processing, protein structure, or music retrieval, to name a few. Procedures for comparing trees are very relevant in many task where tree representations are involved. The computation of these measures is usually a time consuming tasks and different authors have proposed algorithms that are able to compute them in a reasonable time, through approximated versions of the similarity measure. Other methods require that the trees are fully labelled for the distance to be computed. In this paper, a new measure is presented able to deal with trees labelled only at the leaves, that runs in O(|TA|×|TB|) time. Experiments and comparative results are provided.This work was funded by the Spanish DRIMS project (TIN2009-14247-C02), and the research programme Consolider Ingenio 2010 (MIPRCV, CSD2007-00018)

XSLTGen: A system for automatically generating XML transformations via semantic mappings

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