In this paper we seek all real roots of a polynomial with real coefficients and real and nonreal roots. Somewhat paradoxically, one of the most effective solutions is by approximating these real roots semi-numerically...
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ISBN:
(纸本)1595937447
In this paper we seek all real roots of a polynomial with real coefficients and real and nonreal roots. Somewhat paradoxically, one of the most effective solutions is by approximating these real roots semi-numerically together with all nonreal roots. Alternative methods are symbolic, based on Descartes' rule of signs (which can be combined with the continued fraction approximation algorithm) or the Sturm (or Sturm-Habicht) sequences. We combine various old and new techniques to devise semi-numerical algorithms that are effective where the real roots do not lie near the nonreal ones. Copyright 2007 ACM.
With support from HBCU-UP (Historically Black College and University Undergraduate program) at National science Foundation (NSF), the ACTION (Advanced Curriculum and Technology-Based Instructional Opportunities Networ...
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We describe recruitment and selection procedures of the computerscience, Engineering, and mathematics Scholarship (CSEMS) program at the University of Wisconsin-Milwaukee that are designed to attract students who are...
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Chemical reaction networks by which individual cells gather and process information about their chemical environments have been dubbed "signal transduction" networks. Despite this suggestive terminology, the...
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ISBN:
(纸本)9780262195683
Chemical reaction networks by which individual cells gather and process information about their chemical environments have been dubbed "signal transduction" networks. Despite this suggestive terminology, there have been few attempts to analyze chemical signaling systems with the quantitative tools of information theory. Gradient sensing in the social amoeba Dictyostelium discoideum is a well characterized signal transduction system in which a cell estimates the direction of a source of diffusing chemoattractant molecules based on the spatiotemporal sequence of ligand-receptor binding events at the cell membrane. Using Monte Carlo techniques (MCell) we construct a simulation in which a collection of individual ligand particles undergoing Brownian diffusion in a three-dimensional volume interact with receptors on the surface of a static amoeboid cell. Adapting a method for estimation of spike train entropies described by Victor (originally due to Kozachenko and Leonenko), we estimate lower bounds on the mutual information between the transmitted signal (direction of ligand source) and the received signal (spatiotemporal pattern of receptor binding/unbinding events). Hence we provide a quantitative framework for addressing the question: how much could the cell know, and when could it know it? We show that the time course of the mutual information between the cell's surface receptors and the (unknown) gradient direction is consistent with experimentally measured cellular response times. We find that the acquisition of directional information depends strongly on the time constant at which the intracellular response is filtered.
In this paper we consider adaptive workflow nets, a class of nested nets that allows more comfort and expressive power for modeling adaptability and exception handling in workflow nets. We define two important behavio...
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In this paper we consider adaptive workflow nets, a class of nested nets that allows more comfort and expressive power for modeling adaptability and exception handling in workflow nets. We define two important behavioural properties of adaptive workflow nets: soundness and circumspectness. Soundness means that a proper final marking (state) can be reached from any marking which is reachable from the initial marking, and no garbage will be left. Circumspectness means that the upper layer is always ready to handle any exception that can happen in a lower layer. We define a finite state abstraction for adaptive workflow nets and show that soundness and circumspectness can be verified on this abstraction.
Knowledge elicitation is difficult for expert systems that are based on probability theory. The elicitation of probabilities for a probabilistic model requires a lot of time and interaction between the knowledge engin...
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We give a straightforward computable-model-theoretic definition of a property of Δ02 sets called order-computability. We then prove various results about these sets which suggest that, simple though the definition is...
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The authors propose three strategies that are designed to enhance students' understanding and problem-solving ability in introductory mechanics courses: (1) employing multiple-method problem-solving, in which stud...
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For the non-Hermitian and positive semidefinite systems of linear equations, we derive necessary and sufficient conditiorrs for guaranteeing the unconditional convergence of the preconditioned Hermitian and skew-Hermi...
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Lattice Boltzmann algorihms are a mesoscopic representation of nonlinear continuum physics (like Navier-Stokes, magnetohydrodynamics (MHD), Gross-Pitaevskii equations) which are ideal for parallel supercomputers becau...
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