893 resultados para Group theoretical based techniques


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Mathematical models, as instruments for understanding the workings of nature, are a traditional tool of physics, but they also play an ever increasing role in biology - in the description of fundamental processes as well as that of complex systems. In this review, the authors discuss two examples of the application of group theoretical methods, which constitute the mathematical discipline for a quantitative description of the idea of symmetry, to genetics. The first one appears, in the form of a pseudo-orthogonal (Lorentz like) symmetry, in the stochastic modelling of what may be regarded as the simplest possible example of a genetic network and, hopefully, a building block for more complicated ones: a single self-interacting or externally regulated gene with only two possible states: ` on` and ` off`. The second is the algebraic approach to the evolution of the genetic code, according to which the current code results from a dynamical symmetry breaking process, starting out from an initial state of complete symmetry and ending in the presently observed final state of low symmetry. In both cases, symmetry plays a decisive role: in the first, it is a characteristic feature of the dynamics of the gene switch and its decay to equilibrium, whereas in the second, it provides the guidelines for the evolution of the coding rules.

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In all applications of clone detection it is important to have precise and efficient clone identification algorithms. This paper proposes and outlines a new algorithm, KClone for clone detection that incorporates a novel combination of lexical and local dependence analysis to achieve precision, while retaining speed. The paper also reports on the initial results of a case study using an implementation of KClone with which we have been experimenting. The results indi- cate the ability of KClone to find types-1,2, and 3 clones compared to token-based and PDG-based techniques. The paper also reports results of an initial empirical study of the performance of KClone compared to CCFinderX.

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Formal methods and software testing are tools to obtain and control software quality. When used together, they provide mechanisms for software specification, verification and error detection. Even though formal methods allow software to be mathematically verified, they are not enough to assure that a system is free of faults, thus, software testing techniques are necessary to complement the process of verification and validation of a system. Model Based Testing techniques allow tests to be generated from other software artifacts such as specifications and abstract models. Using formal specifications as basis for test creation, we can generate better quality tests, because these specifications are usually precise and free of ambiguity. Fernanda Souza (2009) proposed a method to define test cases from B Method specifications. This method used information from the machine s invariant and the operation s precondition to define positive and negative test cases for an operation, using equivalent class partitioning and boundary value analysis based techniques. However, the method proposed in 2009 was not automated and had conceptual deficiencies like, for instance, it did not fit in a well defined coverage criteria classification. We started our work with a case study that applied the method in an example of B specification from the industry. Based in this case study we ve obtained subsidies to improve it. In our work we evolved the proposed method, rewriting it and adding characteristics to make it compatible with a test classification used by the community. We also improved the method to support specifications structured in different components, to use information from the operation s behavior on the test case generation process and to use new coverage criterias. Besides, we have implemented a tool to automate the method and we have submitted it to more complex case studies

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Conditions for CP violation in the scalar potential sector of general N-Higgs-doublet models are analyzed from a group theoretical perspective. For the simplest two-Higgs-doublet model potential, a minimum set of conditions for explicit and spontaneous CP violation is presented. The conditions can be given a clear geometrical interpretation in terms of quantities in the adjoint representation of the basis transformation group for the two doublets. Such conditions depend on CP-odd pseudoscalar invariants. When the potential is CP invariant, the explicit procedure to reach the real CP-basis and the explicit CP transformation can also be obtained. The procedure to find the real basis and the conditions for CP violation are then extended to general N-Higgs-doublet model potentials. The analysis becomes more involved and only a formal procedure to reach the real basis is found. Necessary conditions for CP invariance can still be formulated in terms of group invariants: the CP-odd generalized pseudoscalars. The problem can be completely solved for three Higgs-doublets.

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We present the zero-temperature phase diagram of the one-dimensional t(2g)-orbital Hubbard model, obtained using the density-matrix renormalization group and Lanczos techniques. Emphasis is given to the case of the electron density n=5 corresponding to five electrons per site, while several other cases for electron densities between n=3 and 6 are also studied. At n=5, our results indicate a first-order transition between a paramagnetic (PM) insulator phase, with power-law slowly decaying correlations, and a fully polarized ferromagnetic (FM) state by tuning the Hund's coupling. The results also suggest a transition from the n=5 PM insulator phase to a metallic regime by changing the electron density, either via hole or electron doping. The behavior of the spin, charge, and orbital correlation functions in the FM and PM states are also described in the text and discussed. The robustness of these two states against varying parameters suggests that they may be of relevance in quasi-one-dimensional Co-oxide materials, or even in higher dimensional cobaltite systems as well.

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Dromion solutions of the Davey-Stewartson equation are analysed from the point of view of the bilinear formalism. The corresponding τ-functions are expressed in terms of vacuum expectation values of Clifford operators and their group-theoretical content is provided. Explicit computation performed with the help of Wick's theorem allows us to characterize the dromion interaction. © 1990.

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Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be in-viable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the bats behaviour, which has never been applied to this context so far. The wrapper approach combines the power of exploration of the bats together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in five public datasets have demonstrated that the proposed approach can outperform some well-known swarm-based techniques. © 2012 IEEE.

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The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different feature vectors, we model the descriptor combination as an optimization problem to be addressed by evolutionary-based techniques, which compute distances between samples that maximize their separability in the feature space. The robustness of the proposed technique is assessed by the Optimum-Path Forest classifier. Experiments showed that the proposed methodology can outperform individual information provided by single descriptors in well-known public datasets. © 2012 IEEE.

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Intense selective pressures applied over short evolutionary time have resulted in homogeneity within, but substantial variation among, horse breeds. Utilizing this population structure, 744 individuals from 33 breeds, and a 54,000 SNP genotyping array, breed-specific targets of selection were identified using an FST-based statistic calculated in 500-kb windows across the genome. A 5.5-Mb region of ECA18, in which the myostatin (MSTN) gene was centered, contained the highest signature of selection in both the Paint and Quarter Horse. Gene sequencing and histological analysis of gluteal muscle biopsies showed a promoter variant and intronic SNP of MSTN were each significantly associated with higher Type 2B and lower Type 1 muscle fiber proportions in the Quarter Horse, demonstrating a functional consequence of selection at this locus. Signatures of selection on ECA23 in all gaited breeds in the sample led to the identification of a shared, 186-kb haplotype including two doublesex related mab transcription factor genes (DMRT2 and 3). The recent identification of a DMRT3 mutation within this haplotype, which appears necessary for the ability to perform alternative gaits, provides further evidence for selection at this locus. Finally, putative loci for the determination of size were identified in the draft breeds and the Miniature horse on ECA11, as well as when signatures of selection surrounding candidate genes at other loci were examined. This work provides further evidence of the importance of MSTN in racing breeds, provides strong evidence for selection upon gait and size, and illustrates the potential for population-based techniques to find genomic regions driving important phenotypes in the modern horse. © 2013 Petersen et al.

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Feature selection aims to find the most important information to save computational efforts and data storage. We formulated this task as a combinatorial optimization problem since the exponential growth of possible solutions makes an exhaustive search infeasible. In this work, we propose a new nature-inspired feature selection technique based on bats behavior, namely, binary bat algorithm The wrapper approach combines the power of exploration of the bats together with the speed of the optimum-path forest classifier to find a better data representation. Experiments in public datasets have shown that the proposed technique can indeed improve the effectiveness of the optimum-path forest and outperform some well-known swarm-based techniques. © 2013 Copyright © 2013 Elsevier Inc. All rights reserved.

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Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)