592 resultados para Complex combinatorial problem
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We first classify the state-of-the-art stream authentication problem in the multicast environment and group them into Signing and MAC approaches. A new approach for authenticating digital streams using Threshold Techniques is introduced. The new approach main advantages are in tolerating packet loss, up to a threshold number, and having a minimum space overhead. It is most suitable for multicast applications running over lossy, unreliable communication channels while, in same time, are pertain the security requirements. We use linear equations based on Lagrange polynomial interpolation and Combinatorial Design methods.
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The purpose of the book is to use Delphi as a vehicle to introduce some fundamental algorithms and to illustrate several mathematical and problem-solving techniques. This book is therefore intended to be more of a reference for problem-solving, with the solution expressed in Delphi. It introduces a somewhat eclectic collection of material, much of which will not be found in a typical book on Pascal or Delphi. Many of the topics have been used by the author over a period of about ten years at Bond University, Australia in various subjects from 1993 to 2003. Much of the work was connected with a data structures subject (second programming course) conducted variously in MODULA-2, Oberon and Delphi, at Bond University, however there is considerable other, more recent material, e.g., a chapter on Sudoku.
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In a traditional anti-jamming system a transmitter who wants to send a signal to a single receiver spreads the signal power over a wide frequency spectrum with the aim of stopping a jammer from blocking the transmission. In this paper, we consider the case that there are multiple receivers and the transmitter wants to broadcast a message to all receivers such that colluding groups of receivers cannot jam the reception of any other receiver. We propose efficient coding methods that achieve this goal and link this problem to well-known problems in combinatorics. We also link a generalisation of this problem to the Key Distribution Pattern problem studied in combinatorial cryptography.
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A set system (X, F ) with X= {x 1,...,x m}) and F = {B1...,B n }, where B i ⊆ X, is called an (n, m) cover-free set system (or CF set system) if for any 1 ≤ i, j, k ≤ n and j ≠ k, |B i >2 |B j ∩ B k | +1. In this paper, we show that CF set systems can be used to construct anonymous membership broadcast schemes (or AMB schemes), allowing a center to broadcast a secret identity among a set of users in a such way that the users can verify whether or not the broadcast message contains their valid identity. Our goal is to construct (n, m) CF set systems in which for given m the value n is as large as possible. We give two constructions for CF set systems, the first one from error-correcting codes and the other from combinatorial designs. We link CF set systems to the concept of cover-free family studied by Erdös et al in early 80’s to derive bounds on parameters of CF set systems. We also discuss some possible extensions of the current work, motivated by different application.
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This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.
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Aspects of Keno modelling throughout the Australian states of Queensland, New South Wales and Victoria are discussed: the trivial Heads or Tails and the more interesting Keno Bonus, which leads to consideration of the subset sum problem. The most intricate structure is where Heads or Tails and Keno Bonus are combined, and here, the issue of independence arises. Closed expressions for expected return to player are presented in each case.
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This paper introduces an integral approach to the study of plasma-surface interactions during the catalytic growth of selected nanostructures (NSs). This approach involves basic understanding of the plasma-specific effects in NS nucleation and growth, theoretical modelling, numerical simulations, plasma diagnostics, and surface microanalysis. Using an example of plasma-assisted growth of surface-supported single-walled carbon nanotubes, we discuss how the combination of these techniques may help improve the outcomes of the growth process. A specific focus here is on the effects of nanoscale plasma-surface interactions on the NS growth and how the available techniques may be used, both in situ and ex situ to optimize the growth process and structural parameters of NSs.
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Realizing the promise of molecularly targeted inhibitors for cancer therapy will require a new level of knowledge about how a drug target is wired into the control circuitry of a complex cellular network. Here we review general homeostatic principles of cellular networks that enable the cell to be resilient in the face of molecular perturbations, while at the same time being sensitive to subtle input signals. Insights into such mechanisms may facilitate the development of combination therapies that take advantage of the cellular control circuitry, with the aim of achieving higher efficacy at a lower drug dosage and with a reduced probability of drug-resistance development.
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A high level of control over quantum dot (QD) properties such as size and composition during fabrication is required to precisely tune the eventual electronic properties of the QD. Nanoscale synthesis efforts and theoretical studies of electronic properties are traditionally treated quite separately. In this paper, a combinatorial approach has been taken to relate the process synthesis parameters and the electron confinement properties of the QDs. First, hybrid numerical calculations with different influx parameters for Si1-x Cx QDs were carried out to simulate the changes in carbon content x and size. Second, the ionization energy theory was applied to understand the electronic properties of Si1-x Cx QDs. Third, stoichiometric (x=0.5) silicon carbide QDs were grown by means of inductively coupled plasma-assisted rf magnetron sputtering. Finally, the effect of QD size and elemental composition were then incorporated in the ionization energy theory to explain the evolution of the Si1-x Cx photoluminescence spectra. These results are important for the development of deterministic synthesis approaches of self-assembled nanoscale quantum confinement structures.
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The response of complex ionized gas systems to the presence of nonuniform distribution of charged grains is investigated using a kinetic model. Contrary to an existing view that the electron temperature inevitably increases in the grain-occupied region because of enhanced ionization to compensate for the electrons lost to the grains, it is shown that this happens only when the ionizing electric field increases in the electron depleted region. The results for two typical plasma systems suggest that when the ionizing electric field depends on the spatially averaged electron density, the electron temperature in the grain containing region can actually decrease.
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A global, or averaged, model for complex low-pressure argon discharge plasmas containing dust grains is presented. The model consists of particle and power balance equations taking into account power loss on the dust grains and the discharge wall. The electron energy distribution is determined by a Boltzmann equation. The effects of the dust and the external conditions, such as the input power and neutral gas pressure, on the electron energy distribution, the electron temperature, the electron and ion number densities, and the dust charge are investigated. It is found that the dust subsystem can strongly affect the stationary state of the discharge by dynamically modifying the electron energy distribution, the electron temperature, the creation and loss of the plasma particles, as well as the power deposition. In particular, the power loss to the dust grains can take up a significant portion of the input power, often even exceeding the loss to the wall.
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A model for electronegative plasmas containing charged dust or colloidal grains was used. Numerical solutions based on the model demonstrate how a low-pressure diffusion equilibrium of the complex electronegative plasma system is dynamically sustained through plasma particle sources.
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A wave propagation in a complex dusty plasma with negative ions was considered. The relevant processes such as ionization, electron attachment, diffusion, positive-negative ion recombination, plasma particle collisions, as well as elastic Coulomb and inelastic dust-charging collisions were taken self-consistently. It was found that the equilibrium of the plasma as well as the propagation of ion waves were modified to various degrees by these effects.
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A generic approach towards tailoring of ion species composition in reactive plasmas used for nanofabrication of various functional nanofilms and nanoassemblies, based on a simplified model of a parallel-plate rf discharge, is proposed. The model includes an idealized reactive plasma containing two neutral and two ionic species interacting via charge exchange collisions in the presence of a microdispersed solid component. It is shown that the number densities of the desired ionic species can be efficiently managed by adjusting the dilution of the working gas in a buffer gas, rates of electron impact ionization, losses of plasma species on the discharge walls, and surfaces of fine particles, charge exchange rates, and efficiency of three-body recombination processes in the plasma bulk. The results are relevant to the plasma-aided nanomanufacturing of ordered patterns of carbon nanotip and nanopyramid microemitters.
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The effect of density and size of dust grains on the electron energy distribution function (EEDF) in low-temperature complex plasmas is studied. It is found that the EEDF depends strongly on the dust density and size. The behavior of the electron temperature can differ significantly from that of a pristine plasma. For low-pressure argon glow discharge, the Druyvesteyn-like EEDF often found in pristine plasmas can become nearly Maxwellian if the dust density and/or sizes are large. One can thus control the plasma parameters by the dust grains.