345 research outputs found

    Using ATL to define advanced and flexible constraint model transformations

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    Transforming constraint models is an important task in re- cent constraint programming systems. User-understandable models are defined during the modeling phase but rewriting or tuning them is manda- tory to get solving-efficient models. We propose a new architecture al- lowing to define bridges between any (modeling or solver) languages and to implement model optimizations. This architecture follows a model- driven approach where the constraint modeling process is seen as a set of model transformations. Among others, an interesting feature is the def- inition of transformations as concept-oriented rules, i.e. based on types of model elements where the types are organized into a hierarchy called a metamodel

    Rewriting Constraint Models with Metamodels

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    An important challenge in constraint programming is to rewrite constraint models into executable programs calculat- ing the solutions. This phase of constraint processing may require translations between constraint programming lan- guages, transformations of constraint representations, model optimizations, and tuning of solving strategies. In this paper, we introduce a pivot metamodel describing the common fea- tures of constraint models including different kinds of con- straints, statements like conditionals and loops, and other first-class elements like object classes and predicates. This metamodel is general enough to cope with the constructions of many languages, from object-oriented modeling languages to logic languages, but it is independent from them. The rewriting operations manipulate metamodel instances apart from languages. As a consequence, the rewriting operations apply whatever languages are selected and they are able to manage model semantic information. A bridge is created between the metamodel space and languages using parsing techniques. Tools from the software engineering world can be useful to implement this framework

    Automatically Discovering Hidden Transformation Chaining Constraints

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    Model transformations operate on models conforming to precisely defined metamodels. Consequently, it often seems relatively easy to chain them: the output of a transformation may be given as input to a second one if metamodels match. However, this simple rule has some obvious limitations. For instance, a transformation may only use a subset of a metamodel. Therefore, chaining transformations appropriately requires more information. We present here an approach that automatically discovers more detailed information about actual chaining constraints by statically analyzing transformations. The objective is to provide developers who decide to chain transformations with more data on which to base their choices. This approach has been successfully applied to the case of a library of endogenous transformations. They all have the same source and target metamodel but have some hidden chaining constraints. In such a case, the simple metamodel matching rule given above does not provide any useful information

    3D Steerable Wavelets in Practice

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    Rewriting Constraint Models with Metamodels

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    International audienceAn important challenge in constraint programming is to rewrite constraint models into executable programs calculat- ing the solutions. This phase of constraint processing may require translations between constraint programming lan- guages, transformations of constraint representations, model optimizations, and tuning of solving strategies. In this paper, we introduce a pivot metamodel describing the common fea- tures of constraint models including different kinds of con- straints, statements like conditionals and loops, and other first-class elements like object classes and predicates. This metamodel is general enough to cope with the constructions of many languages, from object-oriented modeling languages to logic languages, but it is independent from them. The rewriting operations manipulate metamodel instances apart from languages. As a consequence, the rewriting operations apply whatever languages are selected and they are able to manage model semantic information. A bridge is created between the metamodel space and languages using parsing techniques. Tools from the software engineering world can be useful to implement this framework

    Search Strategies for an Anytime Usage of the Branch and Prune Algorithm

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    International audienceWhen applied to numerical CSPs, the branch and prune algorithm (BPA) computes a sharp covering of the solution set. The BPA is therefore impractical when the solution set is large, typically when it has a dimension larger than four or five which is often met in underconstrained problems. The purpose of this paper is to present a new search tree exploration strategy for BPA that hybridizes depth-first and breadth-first searches. This search strategy allows the BPA discovering potential solutions in different areas of the search space in early stages of the exploration, hence allowing an anytime usage of the BPA. The merits of the proposed search strategy are experimentally evaluated

    Solving an Air Conditioning System Problem in an Embodiment Design Context Using Constraint Satisfaction Techniques

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    International audienceIn this paper, the embodiment design of an air condition- ing system (ACS) in an aircraft is investigated using interval constraint satisfaction techniques. The detailed ACS model is quite complex to solve, since it contains many coupled variables and many constraints corresponding to complex physics phenomena. Some new heuristics and notions based on embodiment design knowledge, are briefly introduced to undertake some embodiment design concepts and to obtain a more relevant and more efficient solving process than classical algorithms. The benefits of using constraint programming in embodiment design are discussed and some difficulties for designers using CP tools are shortly detailed

    3D steerable wavelets and monogenic analysis for bioimaging

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    ABSTRACT In this paper we introduce a 3D wavelet frame that has the key property of steerability. The proposed wavelet frame relies on the combination of a 3D isotropic wavelet transform with the 3D Riesz operator which brings steerability to the pyramid. The novel transform enjoys self reversibility and exact steering of the basis functions in any 3D direction by linear combination of the primary coefficients. We exploit the link between the Riesz transform and the directional Hilbert transform to define a multiresolution monogenic signal analysis in 3D which achieves multiscale AM/FM signal decomposition. We give an example of application of the 3D monogenic wavelet frame in biological imaging with the enhancement of anisotropic structures in 3D fluorescence microscopy

    A case of Ureaplasma parvum meningitis in an adult after transphenoidal ablation of craniopharyngioma

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    We report the case of a Ureaplasma parvum meningitis in an immunocompetent patient, 17 days after surgical ablation of a craniopharyngioma. Presence of U. parvum in the cerebrospinal fluid was assessed by 16S rDNA sequencing and U. parvum specific PCR. This article details a surprising complication in an adult of a transphenoidal surgery for ablation of a craniopharyngioma. This is the first case, to our knowledge, of U. parvum meningitis in an adult patient

    An example of in situ ductile damage analysis by tracking algorithm

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    International audienceDamage evolution in ductile metals is characterized by the nucleation, growth and coalescence of small internal voids. Many laws and studies have been developed to understand and predict damage. Numerical modeling, based on full field microstructure acquisition have proven also to be quite efficient. Real microstructure input are of utmost importance as some studies have shown that the deviation from the average behavior for voids growth can be huge and therefore allows a single cavity to drive the damage behavior and lead to failure. We develop the dedicated tool to analyze individually voids during in situ test and use results as input for numerical simulations
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