38 resultados para Topological graph theory.

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Following suggestions of Nekrasov and Siegel, a non-minimal set of fields are added to the pure spinor formalism for the superstring. Twisted (c) over cap = 3 N = 2 generators are then constructed where the pure spinor BRST operator is the fermionic spin-one generator, and the formalism is interpreted as a critical topological string. Three applications of this topological string theory include the super-Poincare covariant computation of multiloop superstring amplitudes without picture-changing operators, the construction of a cubic open superstring field theory without contact-term problems, and a new four-dimensional version of the pure spinor formalism which computes F-terms in the spacetime action.

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Following suggestions of Nekrasov and Siegel, a non-minimal set of fields are added to the pure spinor formalism for the superstring. Twisted ĉ ≤ 3 N ≤ 2 generators are then constructed where the pure spinor BRST operator is the fermionic spin-one generator, and the formalism is interpreted as a critical topological string. Three applications of this topological string theory include the super-Poincaré covariant computation of multiloop superstring amplitudes without picture-changing operators, the construction of a cubic open superstring field theory without contact-term problems, and a new four-dimensional version of the pure spinor formalism which computes F-terms in the spacetime action. © SISSA 2005.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Using the non-minimal version of the pure spinor formalism, manifestly super-Poincare covariant superstring scattering amplitudes can be computed as in topological string theory without the need of picture-changing operators. The only subtlety comes from regularizing the functional integral over the pure spinor ghosts. In this paper, it is shown how to regularize this functional integral in a BRST-invariant manner, allowing the computation of arbitrary multiloop amplitudes. The regularization method simplifies for scattering amplitudes which contribute to ten-dimensional F-terms, i.e. terms in the ten-dimensional superspace action which do not involve integration over the maximum number of theta's.

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This article introduces the software program called EthoSeq, which is designed to extract probabilistic behavioral sequences (tree-generated sequences, or TGSs) from observational data and to prepare a TGS-species matrix for phylogenetic analysis. The program uses Graph Theory algorithms to automatically detect behavioral patterns within the observational sessions. It includes filtering tools to adjust the search procedure to user-specified statistical needs. Preliminary analyses of data sets, such as grooming sequences in birds and foraging tactics in spiders, uncover a large number of TGSs which together yield single phylogenetic trees. An example of the use of the program is our analysis of felid grooming sequences, in which we have obtained 1,386 felid grooming TGSs for seven species, resulting in a single phylogeny. These results show that behavior is definitely useful in phylogenetic analysis. EthoSeq simplifies and automates such analyses, uncovers much of the hidden patterns of long behavioral sequences, and prepares this data for further analysis with standard phylogenetic programs. We hope it will encourage many empirical studies on the evolution of behavior.

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Our objective in this paper is to prove an Implicit Function Theorem for general topological spaces. As a consequence, we show that, under certain conditions, the set of the invertible elements of a topological monoid X is an open topological group in X and we use the classical topological group theory to conclude that this set is a Lie group.

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In this article, we provide invariance conditions for control systems whose dynamics are given by measure driven differential inclusions. The solution concept plays a critical role in the extension of the conventional conditions for the impulsive control context. A couple of examples illustrating the specific features of impulsive control systems are included.

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Throughout this article, it is assumed that the no-central chi-square chart with two stage samplings (TSS Chisquare chart) is employed to monitor a process where the observations from the quality characteristic of interest X are independent and identically normally distributed with mean μ and variance σ2. The process is considered to start with the mean and the variance on target (μ = μ0; σ2 = σ0 2), but at some random time in the future an assignable cause shifts the mean from μ0 to μ1 = μ0 ± δσ0, δ >0 and/or increases the variance from σ0 2 to σ1 2 = γ2σ0 2, γ > 1. Before the assignable cause occurrence, the process is considered to be in a state of statistical control (defined by the in-control state). Similar to the Shewhart charts, samples of size n 0+ 1 are taken from the process at regular time intervals. The samplings are performed in two stages. At the first stage, the first item of the i-th sample is inspected. If its X value, say Xil, is close to the target value (|Xil-μ0|< w0σ 0, w0>0), then the sampling is interrupted. Otherwise, at the second stage, the remaining n0 items are inspected and the following statistic is computed. Wt = Σj=2n 0+1(Xij - μ0 + ξiσ 0)2 i = 1,2 Let d be a positive constant then ξ, =d if Xil > 0 ; otherwise ξi =-d. A signal is given at sample i if |Xil-μ0| > w0σ 0 and W1 > knia:tl, where kChi is the factor used in determining the upper control limit for the non-central chi-square chart. If devices such as go and no-go gauges can be considered, then measurements are not required except when the sampling goes to the second stage. Let P be the probability of deciding that the process is in control and P 1, i=1,2, be the probability of deciding that the process is in control at stage / of the sampling procedure. Thus P = P1 + P 2 - P1P2, P1 = Pr[μ0 - w0σ0 ≤ X ≤ μ0+ w 0σ0] P2=Pr[W ≤ kChi σ0 2], (3) During the in-control period, W / σ0 2 is distributed as a non-central chi-square distribution with n0 degrees of freedom and a non-centrality parameter λ0 = n0d2, i.e. W / σ0 2 - xn0 22 (λ0) During the out-of-control period, W / σ1 2 is distributed as a non-central chi-square distribution with n0 degrees of freedom and a non-centrality parameter λ1 = n0(δ + ξ)2 / γ2 The effectiveness of a control chart in detecting a process change can be measured by the average run length (ARL), which is the speed with which a control chart detects process shifts. The ARL for the proposed chart is easily determined because in this case, the number of samples before a signal is a geometrically distributed random variable with parameter 1-P, that is, ARL = I /(1-P). It is shown that the performance of the proposed chart is better than the joint X̄ and R charts, Furthermore, if the TSS Chi-square chart is used for monitoring diameters, volumes, weights, etc., then appropriate devices, such as go-no-go gauges can be used to decide if the sampling should go to the second stage or not. When the process is stable, and the joint X̄ and R charts are in use, the monitoring becomes monotonous because rarely an X̄ or R value fall outside the control limits. The natural consequence is the user to pay less and less attention to the steps required to obtain the X̄ and R value. In some cases, this lack of attention can result in serious mistakes. The TSS Chi-square chart has the advantage that most of the samplings are interrupted, consequently, most of the time the user will be working with attributes. Our experience shows that the inspection of one item by attribute is much less monotonous than measuring four or five items at each sampling.

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Given that the total amount of losses in a distribution system is known, with a reliable methodology for the technical loss calculation, the non-technical losses can be obtained by subtraction. A usual method of calculation technical losses in the electric utilities uses two important factors: load factor and the loss factor. The load factor is usually obtained with energy and demand measurements, whereas, to compute the loss factor it is necessary the learning of demand and energy loss, which are not, in general, prone of direct measurements. In this work, a statistical analysis of this relationship using the curves of a sampling of consumers in a specific company is presented. These curves will be summarized in different bands of coefficient k. Then, it will be possible determine where each group of consumer has its major concentration of points. ©2008 IEEE.

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This work presents the Petri net-based modeling of an autonomous robot's navigation system used for the application of supplies in agriculture. The model was developed theoretically and implemented through the CPNTools software. It simulates the behavior of the robot, capturing environmental characteristics by means of sensors, making appropriate decisions, and forwarding them to the corresponding actuators. By exciting the model using CPNTools it is possible to simulate situations that the robot might undergo, without the need to expose it to real potentially dangerous situations. ©2009 IEEE.

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The effectiveness of ecological restoration actions toward biodiversity conservation depends on both local and landscape constraints. Extensive information on local constraints is already available, but few studies consider the landscape context when planning restoration actions. We propose a multiscale framework based on the landscape attributes of habitat amount and connectivity to infer landscape resilience and to set priority areas for restoration. Landscapes with intermediate habitat amount and where connectivity remains sufficiently high to favor recolonization were considered to be intermediately resilient, with high possibilities of restoration effectiveness and thus were designated as priority areas for restoration actions. The proposed method consists of three steps: (1) quantifying habitat amount and connectivity; (2) using landscape ecology theory to identify intermediate resilience landscapes based on habitat amount, percolation theory, and landscape connectivity; and (3) ranking landscapes according to their importance as corridors or bottlenecks for biological flows on a broader scale, based on a graph theory approach. We present a case study for the Brazilian Atlantic Forest (approximately 150 million hectares) in order to demonstrate the proposed method. For the Atlantic Forest, landscapes that present high restoration effectiveness represent only 10% of the region, but contain approximately 15 million hectares that could be targeted for restoration actions (an area similar to today's remaining forest extent). The proposed method represents a practical way to both plan restoration actions and optimize biodiversity conservation efforts by focusing on landscapes that would result in greater conservation benefits. © 2013 Society for Ecological Restoration.

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Pós-graduação em Matemática Universitária - IGCE