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On est 37 visiteur(s) en ligneVideo Internet - Stream Invariant
![Recherche de vidéos [Invariant]](http://video.google.com/common/google_logo_small.jpg){kind=logo}  DSD: A Hybrid Analysis Tool for Bug Finding42 mn - 23 juil. 2007 Google TechTalksJuly 13, 2006Christoph CsallnerABSTRACTDSD-Crasher is a bug finding tool that follows a three-step approach to program analysis: D. Capture the program's intended execution behavior with dynamic invariant detection. The derived invariants exclude many unwanted values from the program's input domain. S. Statically analyze the program within the restricted input domain to explore many paths. D. Automatically generate test cases that focus on verifying the results of the static analysis. Thereby confirmed results are never false positives, as opposed to the high false positive rate inherent in conservative static analysis.This three-step approach yields benefits compared to...  AATUCAGG: Lesson 35 - The Equivalence of Massaatucagg 5 mn - 10 oct. 2008 Aatucagg believes that all mass reacts to the curvature of space in the same way because all mass is equivalent  AATUCAGG: Lesson 34 - Invariant and Relativistic Massaatucagg 3 mn - 8 oct. 2008 Invariant and Relativistic Mass are related to the curvature of space by the Aatucagg Factor Longueur inconnue - 30 sept. 2008 Analysis of genetic variation in human populations is critical to the understanding of the genetic basis for complex diseases. Although genomes of several species have been sequenced, it is still too expensive to sequence genomes of several individuals to analyze genetic variation. Furthermore, most of the genome is invariant among individuals. Longueur inconnue - 30 sept. 2008 We will review a selection of graphical representations of proteins and explore their mathematical properties. In particular, we will consider highly condensed representations of proteins by ”magic circle”, representation by star-like graphs and spectral-like representations and will consider calculations of some of acompanying invariants. Finally we will outline graphical approaches to protein alignment. Longueur inconnue - 30 sept. 2008 Longueur inconnue - 30 sept. 2008 Strings play an important role in various sciences, from computer science, linguistics, social sciences, to various natural sciences, including bioinformatics. Strings, words, or finite sequences are mainly studied in formal language theory and form the basis of logic, mathematics and theoretical computer science. Although strings have a simple linear structure, we may associate a number of invariants to them in particular, via various graphs. This non-technical talk will explain some of these features and survey some of the recent work of the present authors. 123 Longueur inconnue - 30 sept. 2008 Systems biologists are interested in modelling chemical reactions in the intracellular environment, and to date much of what is done is based on the use of mass action kinetics to construct models of elementary reactions. Mass action kinetic models are based on a number assumptions which are not obviously valid in the intracellular environment. The cytoplasm is far from an ideal, isotropic wellmixed solution and often the concentrations of important chemical species are very small. Molecular crowding can have significant thermodynamic effects, but also must play an important dynamical role. An interesting approach that has been adopted to this has its roots in fractal geometry - a given molecule, depending upon its size and shape and the sizes and shapes of the molecules which surround it will find itself able to move in an environment of restricted dimension (see for example[1, 2]). Simple ideas have been suggested which give spatially homogeneous rate-like equations which attempt to account for this. It has been suggested, for example, that rate laws which depend on non-integer powers of the concentration of species might be used, and alternatively that the rate constants for elementary reactions which involve the encounter of different species (as opposed to spontaneous decomposition of individual molecules) should be time-dependent[1]. In this case the rates decay in time - the suggested form is the Zipf-Mandlebrot law which tends to a power law decay at long times, it is suggested that this power law characterises the dimension of the restricted environment of each chemical species[2]. Both of these approaches suffer from shortcomings. The use of non-integer powers of concentrations can only be justified in very limited circumstances, and has been shown to be inferior to the time-dependent rate parameter when describing certain lattice gas computer simulations of chemical reactions. However, the latter is clearly not invariant to time translation - the origin of time has a particular significance, and it is not clear as a general principle what the correct choice of time origin should be. Moreover, experimental techniques are being refined to the extent that spatio-temporal resolution of the species within a single cell is becoming possible. We might, therefore, aspire to constructing theories which describe the dynamics for spatially non-uniform distributions of active species. We have recently been working on a class of simple models of this type. These are spatio-temporal dynamical systems which model reaction and diffusion on a certain class of fractal sets. It has been known for some time now that it is possible to define random walks, and hence diffusion, on a certain class of fractals (indeed, it was this observation that motivated the work described above[1]). A simple example if this class is the Sierpinsky Gasket which has constrictions to the diffusion process in the sense that it can be disconnected by the removal of a finite set of points. The talk will focus mainly on this example, but we shall also suggest ways which could lead to more general models. Supported by the Manchester Institute for Mathematical Science (MIMS). Longueur inconnue - 30 sept. 2008 In the "structural" paradigm for visual pattern recognition, or what some call "strong" pattern recognition, one is not satisfied with simply assigning a class label to an input object, but instead we aim at finding exactly which parts of the template object correspond to which parts of the scene. This is a much harder problem in principle, because it is inherently combinatorial on the number of parts (features) involved, both in the template object and in the scene. This talk describes a summary of our research efforts in setting this as a mathematical optimization problem and solving it efficiently by exploiting geometric constraints. The key insight involves encoding geometric constraints as conditional independency assumptions in a probabilistic graphical model. Due to some geometric facts, it is possible to show that such models are very well behaved: they allow for exact probabilistic inference in polynomial time. The result is a unified framework for structural visual pattern recognition that is able to handle in a principled way a variety of problems, including point pattern matching in its many instances: invariant to translations, isometries, scalings, affine or projective transformations. Attributed graph matching problems, such as matching road networks, can also be solved within such framework. Limitations and future directions will be discussed. Longueur inconnue - 30 sept. 2008 The proposed method uses homonymous and heteronymous examplepairs to train a linear preprocessor on a kernel-induced Hilbert space. The algorithm seeks to optimize the expected performance of elementary classifiers to be generated from single future training examples. The method is justified by PAC-style generalization guarantees and the resulting algorithm has been tested on problems of geometrically invariant pattern recognition and face verification. |
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