112 resultados para GALAXIES: FUNDAMENTAL PARAMETERS


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The development of an expert system, BRIDEX, for the design of prestressed concrete bridges is discussed in this paper. Design of multi-span continuous pre-stressed concrete bridges pose considerable difficulties to designers because of the large number of parameters involved and their complex interactions. The design is often perceived as an iterative process of generation, evaluation and modification of trial designs. It takes years of experience to develop an understanding of the design process. BRIDEX is aimed at providing guidance to the designers by suggesting appropriate range of values for the design parameters. The knowledge within BRIDEX is mainly based on fundamental principles developed by a careful study of the intricacies involved in the design process, while heuristics are used only to supplement this knowledge. The BRIDEX approach ensures that the whole design evolves sequentially as the design proceeds, module after module.

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Oscillation processes have been revealed in the course of reversible polarization study in ferroelectric liquid crystals. The oscillation frequency of polarization vector has been found to be from 1 to 30 kHz. The oscillation parameters were studied as functions of temperature. Temperature dependences of the oscillation amplitude and damping decrement have been measured.

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Model-based optical motion capture systems require knowledge of the position of the markers relative to the underlying skeleton, the lengths of the skeleton's limbs, and which limb each marker is attached to. These model parameters are typically assumed and entered into the system manually, although techniques exist for calculating some of them, such as the position of the markers relative to the skeleton's joints. We present a fully automatic procedure for determining these model parameters. It tracks the 2D positions of the markers on the cameras' image planes and determines which markers lie on each limb before calculating the position of the underlying skeleton. The only assumption is that the skeleton consists of rigid limbs connected with ball joints. The proposed system is demonstrated on a number of real data examples and is shown to calculate good estimates of the model parameters in each. © 2004 Elsevier B.V. All rights reserved.

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This paper proposes a Bayesian method for polyphonic music description. The method first divides an input audio signal into a series of sections called snapshots, and then estimates parameters such as fundamental frequencies and amplitudes of the notes contained in each snapshot. The parameter estimation process is based on a frequency domain modelling and Gibbs sampling. Experimental results obtained from audio signals of test note patterns are encouraging; the accuracy is better than 80% for the estimation of fundamental frequencies in terms of semitones and instrument names when the number of simultaneous notes is two.

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Experiments were conducted investigating the interaction between a normal shock wave and a corner boundary layer in a constant area rectangular duct. Active corner suction and passive blowing were applied to manipulate the natural corner flows developing in the working section of the Cambridge University supersonic wind tunnel. In addition robust vane micro-vortex generators were applied to the corners of the working section. Experiments were conducted at Mach numbers of M∞=1.4 and 1.5. Flow visualisation was carried out through schlieren and surface oil flow, while static pressures were recorded via floor tappings. The results indicate that an interplay occurs between the corner flow and the centre line flow. It is believed that corner flow separation acts to induce a shock bifurcation, which in turn leads to a smearing of the adverse pressure gradient elsewhere. In addition the blockage effect from the corners was seen to result in a reacceleration of the subsonic post-shock flow. As a result manipulation of the corner regions allows a separated or attached centre line flow to be observed at the same Mach number. Copyright © 2010 by Babinsky, Burton, Bruce.

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This article presents a novel algorithm for learning parameters in statistical dialogue systems which are modeled as Partially Observable Markov Decision Processes (POMDPs). The three main components of a POMDP dialogue manager are a dialogue model representing dialogue state information; a policy that selects the system's responses based on the inferred state; and a reward function that specifies the desired behavior of the system. Ideally both the model parameters and the policy would be designed to maximize the cumulative reward. However, while there are many techniques available for learning the optimal policy, no good ways of learning the optimal model parameters that scale to real-world dialogue systems have been found yet. The presented algorithm, called the Natural Actor and Belief Critic (NABC), is a policy gradient method that offers a solution to this problem. Based on observed rewards, the algorithm estimates the natural gradient of the expected cumulative reward. The resulting gradient is then used to adapt both the prior distribution of the dialogue model parameters and the policy parameters. In addition, the article presents a variant of the NABC algorithm, called the Natural Belief Critic (NBC), which assumes that the policy is fixed and only the model parameters need to be estimated. The algorithms are evaluated on a spoken dialogue system in the tourist information domain. The experiments show that model parameters estimated to maximize the expected cumulative reward result in significantly improved performance compared to the baseline hand-crafted model parameters. The algorithms are also compared to optimization techniques using plain gradients and state-of-the-art random search algorithms. In all cases, the algorithms based on the natural gradient work significantly better. © 2011 ACM.

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Novel statistical models are proposed and developed in this paper for automated multiple-pitch estimation problems. Point estimates of the parameters of partial frequencies of a musical note are modeled as realizations from a non-homogeneous Poisson process defined on the frequency axis. When several notes are combined, the processes for the individual notes combine to give a new Poisson process whose likelihood is easy to compute. This model avoids the data-association step of linking the harmonics of each note with the corresponding partials and is ideal for efficient Bayesian inference of unknown multiple fundamental frequencies in a signal. © 2011 IEEE.

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It has previously been shown that MD streaks are created in the headbox jet, which is closely connected to the appearance of waves on the jet surface. The fundamental mechanism behind this break-up is presented. This has been achieved by implementing state-of-the-art methods for determining the characteristics and evolution of hydrody-namic instabilities. The methodology also allows the headbox slice to be designed in order to minimise jet break-up. This possibility has been evaluated in pilot-scale.