20 resultados para Decomposable Ordered Set

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Non-linear methods for estimating variability in time-series are currently of widespread use. Among such methods are approximate entropy (ApEn) and sample approximate entropy (SampEn). The applicability of ApEn and SampEn in analyzing data is evident and their use is increasing. However, consistency is a point of concern in these tools, i.e., the classification of the temporal organization of a data set might indicate a relative less ordered series in relation to another when the opposite is true. As highlighted by their proponents themselves, ApEn and SampEn might present incorrect results due to this lack of consistency. In this study, we present a method which gains consistency by using ApEn repeatedly in a wide range of combinations of window lengths and matching error tolerance. The tool is called volumetric approximate entropy, vApEn. We analyze nine artificially generated prototypical time-series with different degrees of temporal order (combinations of sine waves, logistic maps with different control parameter values, random noises). While ApEn/SampEn clearly fail to consistently identify the temporal order of the sequences, vApEn correctly do. In order to validate the tool we performed shuffled and surrogate data analysis. Statistical analysis confirmed the consistency of the method. (C) 2008 Elsevier Ltd. All rights reserved.

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Clustering is a difficult task: there is no single cluster definition and the data can have more than one underlying structure. Pareto-based multi-objective genetic algorithms (e.g., MOCK Multi-Objective Clustering with automatic K-determination and MOCLE-Multi-Objective Clustering Ensemble) were proposed to tackle these problems. However, the output of such algorithms can often contains a high number of partitions, becoming difficult for an expert to manually analyze all of them. In order to deal with this problem, we present two selection strategies, which are based on the corrected Rand, to choose a subset of solutions. To test them, they are applied to the set of solutions produced by MOCK and MOCLE in the context of several datasets. The study was also extended to select a reduced set of partitions from the initial population of MOCLE. These analysis show that both versions of selection strategy proposed are very effective. They can significantly reduce the number of solutions and, at the same time, keep the quality and the diversity of the partitions in the original set of solutions. (C) 2010 Elsevier B.V. All rights reserved.

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This paper deals with semi-global C(k)-solvability of complex vector fields of the form L = partial derivative/partial derivative t + x(r) (a(x) + ib(x))partial derivative/partial derivative x, r >= 1, defined on Omega(epsilon) = (-epsilon, epsilon) x S(1), epsilon > 0, where a and b are C(infinity) real-valued functions in (-epsilon, epsilon). It is shown that the interplay between the order of vanishing of the functions a and b at x = 0 influences the C(k)-solvability at Sigma = {0} x S(1). When r = 1, it is permitted that the functions a and b of L depend on the x and t variables, that is, L = partial derivative/partial derivative t + x(a(x, t) + ib(x, t))partial derivative/partial derivative x, where (x, t) is an element of Omega(epsilon).

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We study the Gevrey solvability of a class of complex vector fields, defined on Omega(epsilon) = (-epsilon, epsilon) x S(1), given by L = partial derivative/partial derivative t + (a(x) + ib(x))partial derivative/partial derivative x, b not equivalent to 0, near the characteristic set Sigma = {0} x S(1). We show that the interplay between the order of vanishing of the functions a and b at x = 0 plays a role in the Gevrey solvability. (C) 2008 Elsevier Inc. All rights reserved.

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In this paper we describe and evaluate a geometric mass-preserving redistancing procedure for the level set function on general structured grids. The proposed algorithm is adapted from a recent finite element-based method and preserves the mass by means of a localized mass correction. A salient feature of the scheme is the absence of adjustable parameters. The algorithm is tested in two and three spatial dimensions and compared with the widely used partial differential equation (PDE)-based redistancing method using structured Cartesian grids. Through the use of quantitative error measures of interest in level set methods, we show that the overall performance of the proposed geometric procedure is better than PDE-based reinitialization schemes, since it is more robust with comparable accuracy. We also show that the algorithm is well-suited for the highly stretched curvilinear grids used in CFD simulations. Copyright (C) 2010 John Wiley & Sons, Ltd.

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A method for linearly constrained optimization which modifies and generalizes recent box-constraint optimization algorithms is introduced. The new algorithm is based on a relaxed form of Spectral Projected Gradient iterations. Intercalated with these projected steps, internal iterations restricted to faces of the polytope are performed, which enhance the efficiency of the algorithm. Convergence proofs are given and numerical experiments are included and commented. Software supporting this paper is available through the Tango Project web page: http://www.ime.usp.br/similar to egbirgin/tango/.

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This paper deals with the classical one-dimensional integer cutting stock problem, which consists of cutting a set of available stock lengths in order to produce smaller ordered items. This process is carried out in order to optimize a given objective function (e.g., minimizing waste). Our study deals with a case in which there are several stock lengths available in limited quantities. Moreover, we have focused on problems of low demand. Some heuristic methods are proposed in order to obtain an integer solution and compared with others. The heuristic methods are empirically analyzed by solving a set of randomly generated instances and a set of instances from the literature. Concerning the latter. most of the optimal solutions of these instances are known, therefore it was possible to compare the solutions. The proposed methods presented very small objective function value gaps. (C) 2008 Elsevier Ltd. All rights reserved.

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In 2006, the first report of a nanostructured material as adjuvant was described establishing the effectiveness of the ordered mesoporous SBA-15 silica as an immune adjuvant. The present study evaluated the SBA-15 capacity to modulate the immune responsiveness of High and Low responder mice immunized with BSA encapsulated/adsorbed in SBA-15 by the intramuscular or oral route and the adjuvant effect was compared with the responsiveness induced by BSA in aluminum hydroxide salts or emulsified in Incomplete Freund adjuvant. These results demonstrate the ability of the non-toxic SBA-15 nanoparticles to increase the immunogenicity and repair the responsiveness of the constitutively low responder individuals inducing both the IgG2a and the IgG1 isotypes, independently of the immune cell committed and conditioning the low phenotype. This new adjuvant may reveal novel therapeutic targets for immune modulation and vaccine design. (C) 2010 Elsevier Ltd. All rights reserved.

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Iron was successfully incorporated in FDU-1 type cubic ordered mesoporous silica by a simple direct synthesis route. The (Fe/FDU-1) samples were characterized by Rutherford back-scattering spectrometry (RBS), small angle X-ray scattering (SAXS). N(2) sorption isotherm, X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS). The resulting material presented an iron content of about 5%. Prepared at the usual acid pH of -0.3, the composite was mostly formed by amorphous silica and hematite with a quantity of Fe(2+) present in the structure. The samples prepared with adjusted pH values (2 and 3.5) were amorphous. The samples` average pore diameter was around 12.0 nm and BET specific surface area was of 680 m(2) g(-1). Although the iron-incorporated material presented larger lattice parameter, about 25 nm compared to pure FDU-1, the Fe/FDU-1 composite still maintained its cubic ordered fcc mesoporous structure before and after the template removal at 540 degrees C. The catalytic performance of Fe/FDU-1 was investigated in the catalytic oxidation of Black Remazol B dye using a catalytic ozonation process. The results indicated that Fe/FDU-1 prepared at the usual acid pH exhibited high catalytic activity in the mineralization of this pollutant when compared to the pure FDU-1. Fe(2)O(3) and Fe/FDU-1 prepared with higher pH of 2 and 3.5. (C) 2010 Elsevier B.V. All rights reserved.

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Large pore ordered mesoporous silica FDU-1 with three-dimensional (3D) face-centered cubic, Fm3m arrangement of rnesopores, was synthesized under strong acid media using B-50-6600 poly(ethylene oxide)-poly(butylene oxide)-poly(ethylene oxide) triblock copolymer (EO(39)BO(47)EO(39)), tetraethyl orthosilicate (TEOS) and trimethyl-benzene (TMB). Large pore FDU-1 silica was obtained by using the following gel composition 1TEOS:0.00735B50-6600:0.00735TMB:6HCl:155H(2)O. The pristine material exhibited a BET specific surface area of 684 m(2) g(-1), total pore volume of 0.89 cm(3) g(-1), external surface area of 49 m(2) g(-1) and microporous volume of 0.09 cm(3) g(-1). The enzyme activity was determined by the Flow Injection Analysis-Chemiluminescence (FIA-CL) method. For GOD immobilized on the FDU-1 silica, GOD supernatant and GOD solution, the FIA-CL results were 9.0, 18.6 and 34.0 U, respectively. The value obtained for the activity of the GOD solution with FIA-CL method is in agreement with the 35 U, obtained by spectrophotometry. (C) 2011 Elsevier B.V. All rights reserved.

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Magnetic M( T, H, P) and electrical transport.( T, H, P) measurements in a strong spin-lattice-charge coupled La(0.7)Ca(0.3)MnO(3) system have been conducted. The application of H and P leads to the formation of different magnetic domain structures in the vicinity and below the polaronic-to-ferromagnetic transition temperature. The charge mobility is more sensitive to the variation of the spatial wave function overlap between Mn(3+) eg and O(2-) 2p orbitals due to the applied compacting pressure rather than the relative spin orientation between neighbouring Mn ions when the magnetic field is applied. In spite of the presence of different magnetic domain structures due to the sample history, the effect of magnetic field and pressure is less pronounced at lower temperatures on electrical transport properties.

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In this paper, we use Nuclear Magnetic Resonance (NMR) to write electronic states of a ferromagnetic system into high-temperature paramagnetic nuclear spins. Through the control of phase and duration of radio frequency pulses, we set the NMR density matrix populations, and apply the technique of quantum state tomography to experimentally obtain the matrix elements of the system, from which we calculate the temperature dependence of magnetization for different magnetic fields. The effects of the variation of temperature and magnetic field over the populations can be mapped in the angles of spin rotations, carried out by the RF pulses. The experimental results are compared to the Brillouin functions of ferromagnetic ordered systems in the mean field approximation for two cases: the mean field is given by (i) B = B(0) + lambda M and (ii) B = B(0) + lambda M + lambda`M(3), where B(0) is the external magnetic field, and lambda, lambda` are mean field parameters. The first case exhibits second order transition, whereas the second case has first order transition with temperature hysteresis. The NMR simulations are in good agreement with the magnetic predictions.

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Global optimization seeks a minimum or maximum of a multimodal function over a discrete or continuous domain. In this paper, we propose a hybrid heuristic-based on the CGRASP and GENCAN methods-for finding approximate solutions for continuous global optimization problems subject to box constraints. Experimental results illustrate the relative effectiveness of CGRASP-GENCAN on a set of benchmark multimodal test functions.

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A bipartite graph G = (V, W, E) is convex if there exists an ordering of the vertices of W such that, for each v. V, the neighbors of v are consecutive in W. We describe both a sequential and a BSP/CGM algorithm to find a maximum independent set in a convex bipartite graph. The sequential algorithm improves over the running time of the previously known algorithm and the BSP/CGM algorithm is a parallel version of the sequential one. The complexity of the algorithms does not depend on |W|.

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We explicitly construct a stationary coupling attaining Ornstein`s (d) over bar -distance between ordered pairs of binary chains of infinite order. Our main tool is a representation of the transition probabilities of the coupled bivariate chain of infinite order as a countable mixture of Markov transition probabilities of increasing order. Under suitable conditions on the loss of memory of the chains, this representation implies that the coupled chain can be represented as a concatenation of i.i.d. sequences of bivariate finite random strings of symbols. The perfect simulation algorithm is based on the fact that we can identify the first regeneration point to the left of the origin almost surely.