903 resultados para Affine Blocking Sets


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Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

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Cette thèse présente une étude dans divers domaines de l'informatique théorique de modèles de calculs combinant automates finis et contraintes arithmétiques. Nous nous intéressons aux questions de décidabilité, d'expressivité et de clôture, tout en ouvrant l'étude à la complexité, la logique, l'algèbre et aux applications. Cette étude est présentée au travers de quatre articles de recherche. Le premier article, Affine Parikh Automata, poursuit l'étude de Klaedtke et Ruess des automates de Parikh et en définit des généralisations et restrictions. L'automate de Parikh est un point de départ de cette thèse; nous montrons que ce modèle de calcul est équivalent à l'automate contraint que nous définissons comme un automate qui n'accepte un mot que si le nombre de fois que chaque transition est empruntée répond à une contrainte arithmétique. Ce modèle est naturellement étendu à l'automate de Parikh affine qui effectue une opération affine sur un ensemble de registres lors du franchissement d'une transition. Nous étudions aussi l'automate de Parikh sur lettres: un automate qui n'accepte un mot que si le nombre de fois que chaque lettre y apparaît répond à une contrainte arithmétique. Le deuxième article, Bounded Parikh Automata, étudie les langages bornés des automates de Parikh. Un langage est borné s'il existe des mots w_1, w_2, ..., w_k tels que chaque mot du langage peut s'écrire w_1...w_1w_2...w_2...w_k...w_k. Ces langages sont importants dans des domaines applicatifs et présentent usuellement de bonnes propriétés théoriques. Nous montrons que dans le contexte des langages bornés, le déterminisme n'influence pas l'expressivité des automates de Parikh. Le troisième article, Unambiguous Constrained Automata, introduit les automates contraints non ambigus, c'est-à-dire pour lesquels il n'existe qu'un chemin acceptant par mot reconnu par l'automate. Nous montrons qu'il s'agit d'un modèle combinant une meilleure expressivité et de meilleures propriétés de clôture que l'automate contraint déterministe. Le problème de déterminer si le langage d'un automate contraint non ambigu est régulier est montré décidable. Le quatrième article, Algebra and Complexity Meet Contrained Automata, présente une étude des représentations algébriques qu'admettent les automates contraints et les automates de Parikh affines. Nous déduisons de ces caractérisations des résultats d'expressivité et de complexité. Nous montrons aussi que certaines hypothèses classiques en complexité computationelle sont reliées à des résultats de séparation et de non clôture dans les automates de Parikh affines. La thèse est conclue par une ouverture à un possible approfondissement, au travers d'un certain nombre de problèmes ouverts.

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This paper discusses our research in developing a generalized and systematic method for anomaly detection. The key ideas are to represent normal program behaviour using system call frequencies and to incorporate probabilistic techniques for classification to detect anomalies and intrusions. Using experiments on the sendmail system call data, we demonstrate that concise and accurate classifiers can be constructed to detect anomalies. An overview of the approach that we have implemented is provided.

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The median (antimedian) set of a profile π = (u1, . . . , uk) of vertices of a graphG is the set of vertices x that minimize (maximize) the remoteness i d(x,ui ). Two algorithms for median graphs G of complexity O(nidim(G)) are designed, where n is the order and idim(G) the isometric dimension of G. The first algorithm computes median sets of profiles and will be in practice often faster than the other algorithm which in addition computes antimedian sets and remoteness functions and works in all partial cubes

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This paper highlights the prediction of learning disabilities (LD) in school-age children using rough set theory (RST) with an emphasis on application of data mining. In rough sets, data analysis start from a data table called an information system, which contains data about objects of interest, characterized in terms of attributes. These attributes consist of the properties of learning disabilities. By finding the relationship between these attributes, the redundant attributes can be eliminated and core attributes determined. Also, rule mining is performed in rough sets using the algorithm LEM1. The prediction of LD is accurately done by using Rosetta, the rough set tool kit for analysis of data. The result obtained from this study is compared with the output of a similar study conducted by us using Support Vector Machine (SVM) with Sequential Minimal Optimisation (SMO) algorithm. It is found that, using the concepts of reduct and global covering, we can easily predict the learning disabilities in children

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A profile is a finite sequence of vertices of a graph. The set of all vertices of the graph which minimises the sum of the distances to the vertices of the profile is the median of the profile. Any subset of the vertex set such that it is the median of some profile is called a median set. The number of median sets of a graph is defined to be the median number of the graph. In this paper, we identify the median sets of various classes of graphs such as Kp − e, Kp,q forP > 2, and wheel graph and so forth. The median numbers of these graphs and hypercubes are found out, and an upper bound for the median number of even cycles is established.We also express the median number of a product graph in terms of the median number of their factors.

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For a set S of vertices and the vertex v in a connected graph G, max x2S d(x, v) is called the S-eccentricity of v in G. The set of vertices with minimum S-eccentricity is called the S-center of G. Any set A of vertices of G such that A is an S-center for some set S of vertices of G is called a center set. We identify the center sets of certain classes of graphs namely, Block graphs, Km,n, Kn −e, wheel graphs, odd cycles and symmetric even graphs and enumerate them for many of these graph classes. We also introduce the concept of center number which is defined as the number of distinct center sets of a graph and determine the center number of some graph classes

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Given a non empty set S of vertices of a graph, the partiality of a vertex with respect to S is the di erence between maximum and minimum of the distances of the vertex to the vertices of S. The vertices with minimum partiality constitute the fair center of the set. Any vertex set which is the fair center of some set of vertices is called a fair set. In this paper we prove that the induced subgraph of any fair set is connected in the case of trees and characterise block graphs as the class of chordal graphs for which the induced subgraph of all fair sets are connected. The fair sets of Kn, Km;n, Kn e, wheel graphs, odd cycles and symmetric even graphs are identi ed. The fair sets of the Cartesian product graphs are also discussed

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Relativistic density functional theory is widely applied in molecular calculations with heavy atoms, where relativistic and correlation effects are on the same footing. Variational stability of the Dirac Hamiltonian is a very important field of research from the beginning of relativistic molecular calculations on, among efforts for accuracy, efficiency, and density functional formulation, etc. Approximations of one- or two-component methods and searching for suitable basis sets are two major means for good projection power against the negative continuum. The minimax two-component spinor linear combination of atomic orbitals (LCAO) is applied in the present work for both light and super-heavy one-electron systems, providing good approximations in the whole energy spectrum, being close to the benchmark minimax finite element method (FEM) values and without spurious and contaminated states, in contrast to the presence of these artifacts in the traditional four-component spinor LCAO. The variational stability assures that minimax LCAO is bounded from below. New balanced basis sets, kinetic and potential defect balanced (TVDB), following the minimax idea, are applied with the Dirac Hamiltonian. Its performance in the same super-heavy one-electron quasi-molecules shows also very good projection capability against variational collapse, as the minimax LCAO is taken as the best projection to compare with. The TVDB method has twice as many basis coefficients as four-component spinor LCAO, which becomes now linear and overcomes the disadvantage of great time-consumption in the minimax method. The calculation with both the TVDB method and the traditional LCAO method for the dimers with elements in group 11 of the periodic table investigates their difference. New bigger basis sets are constructed than in previous research, achieving high accuracy within the functionals involved. Their difference in total energy is much smaller than the basis incompleteness error, showing that the traditional four-spinor LCAO keeps enough projection power from the numerical atomic orbitals and is suitable in research on relativistic quantum chemistry. In scattering investigations for the same comparison purpose, the failure of the traditional LCAO method of providing a stable spectrum with increasing size of basis sets is contrasted to the TVDB method, which contains no spurious states already without pre-orthogonalization of basis sets. Keeping the same conditions including the accuracy of matrix elements shows that the variational instability prevails over the linear dependence of the basis sets. The success of the TVDB method manifests its capability not only in relativistic quantum chemistry but also for scattering and under the influence of strong external electronic and magnetic fields. The good accuracy in total energy with large basis sets and the good projection property encourage wider research on different molecules, with better functionals, and on small effects.

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We investigate solution sets of a special kind of linear inequality systems. In particular, we derive characterizations of these sets in terms of minimal solution sets. The studied inequalities emerge as information inequalities in the context of Bayesian networks. This allows to deduce important properties of Bayesian networks, which is important within causal inference.

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We investigate the differences --- conceptually and algorithmically --- between affine and projective frameworks for the tasks of visual recognition and reconstruction from perspective views. It is shown that an affine invariant exists between any view and a fixed view chosen as a reference view. This implies that for tasks for which a reference view can be chosen, such as in alignment schemes for visual recognition, projective invariants are not really necessary. We then use the affine invariant to derive new algebraic connections between perspective views. It is shown that three perspective views of an object are connected by certain algebraic functions of image coordinates alone (no structure or camera geometry needs to be involved).

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El presente documento es el producto de un análisis en cuanto al área de Logística Inversa del grupo empresarial AMAREY, el cual cuenta en la actualidad con más de dieciséis sistemas de sets quirúrgicos de ortopedia, es decir: sistema para mano, pie, radio, cadera, tibia, hombro, entre otros; de los cuales se tienen una cantidad específica de cada sistema, es decir: 4 sets del sistema Axsos. Se encuentra que la compañía no cuenta con ningún tipo de ayuda que le pueda brindar información exacta y a tiempo sobre las entradas y las salidas de los equipos de cirugía. Por lo anterior el resultado de la investigación está orientada a proponer la implementación de sistemas de información en los proceso de logística inversa de los sets quirúrgicos de ortopedia, con el fin de obtener una mejor gestión de la calidad al realizar la trazabilidad del material crítico y del set en general.

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Asset correlations are of critical importance in quantifying portfolio credit risk and economic capitalin financial institutions. Estimation of asset correlation with rating transition data has focusedon the point estimation of the correlation without giving any consideration to the uncertaintyaround these point estimates. In this article we use Bayesian methods to estimate a dynamicfactor model for default risk using rating data (McNeil et al., 2005; McNeil and Wendin, 2007).Bayesian methods allow us to formally incorporate human judgement in the estimation of assetcorrelation, through the prior distribution and fully characterize a confidence set for the correlations.Results indicate: i) a two factor model rather than the one factor model, as proposed bythe Basel II framework, better represents the historical default data. ii) importance of unobservedfactors in this type of models is reinforced and point out that the levels of the implied asset correlationscritically depend on the latent state variable used to capture the dynamics of default,as well as other assumptions on the statistical model. iii) the posterior distributions of the assetcorrelations show that the Basel recommended bounds, for this parameter, undermine the levelof systemic risk.

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Topological indices have been applied to build QSAR models for a set of 20 antimalarial cyclic peroxy cetals. In order to evaluate the reliability of the proposed linear models leave-n-out and Internal Test Sets (ITS) approaches have been considered. The proposed procedure resulted in a robust and consensued prediction equation and here it is shown why it is superior to the employed standard cross-validation algorithms involving multilinear regression models

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This paper discusses a study conducted to test sound discrimination abilities of the chinchilla.