29 resultados para model confidence set


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Based on the extended Huygens-Fresnel principle, the mutual coherence function of quasi-monochromatic electromagnetic Gaussian Schell-model (EGSM) beams propagating through turbulent atmosphere is derived analytically. By employing the lateral and the longitudinal coherence length of EGSM beams to characterize the spatial and the temporal coherence of the beams, the behavior of changes in the spatial and the temporal coherence of those beams is studied. The results show that with a fixed set of beam parameters and under particular atmospheric turbulence model, the lateral coherence of an EGSM beam reaches its maximum value as the beam propagates a certain distance in the turbulent atmosphere, then it begins degrading and keeps decreasing along with the further distance. However, the longitudinal coherence length of an EGSM beam keeps unchanging in this propagation. Lastly, a qualitative explanation is given to these results. (c) 2007 Elsevier B.V. All rights reserved.

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The traditional monostable-bistable transition logic element (MOBILE) structure is usually composed of resonant tunneling diodes (RTD). This letter describes a new type MOBILE structure consisting of single-electron transistors (i.e. SET-MOBILE). The analytical model of single-electron transistors ( SET) has been considered three states (including an excited state) of the discrete quantum energy levels. The simulation results show negative differential conductance (NDC) characteristics in I-DS-V-DS curve. The SET-MOBILE utilizing NDC characteristics can successfully realize the basic logic functions as the RTD-MOBILE.

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Knowledge management is a critical issue for the next-generation web application, because the next-generation web is becoming a semantic web, a knowledge-intensive network. XML Topic Map (XTM), a new standard, is appearing in this field as one of the structures for the semantic web. It organizes information in a way that can be optimized for navigation. In this paper, a new set of hyper-graph operations on XTM (HyO-XTM) is proposed to manage the distributed knowledge resources.HyO-XTM is based on the XTM hyper-graph model. It is well applied upon XTM to simplify the workload of knowledge management.The application of the XTM hyper-graph operations is demonstrated by the knowledge management system of a consulting firm. HyO-XTM shows the potential to lead the knowledge management to the next-generation web.

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Our Agent-based Software Process Modelling (ASPM) approach describes a software process as a set of cooperative agents. Negotiation is the way in which the agents construct their cooperative relations, and thus the software process. Currently, most negotiation models use a fixed negotiation protocol and fixed strategies. In order to achieve the flexibility that the negotiation of the agents in ASPM requires, we propose a negotiation model NM-PA. NM-PA mainly includes a generic negotiation protocol and some rules, which possibly change in different negotiation processes. By changing the rules, the model can support multi-protocols and multi-decision-making strategies at a lower cost.

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Based on Fresnel-Mrchhoff diffraction theory, a diffraction model of nonlinear optical media interacting with a Gaussian beam has been set up that can interpret the Z-scan phenomenon in a new way. This theory not only is consistent with the conventional Z-scan theory for a small nonlinear phase shift but also can be used for larger nonlinear phase shifts. Numerical computations indicate that the shape of the Z-scan curve is greatly affected by the value of the nonlinear phase shift. The symmetric dispersionlike Z-scan curve is valid only for small nonlinear p base shifts (\Deltaphi(0)\ < pi), but, with increasingly larger nonlinear phase shifts, the valley of the transmittance is severely suppressed and the peak is greatly enhanced. The power output through the aperture will oscillate with increasing nonlinear phase shift caused by the input laser power. The aperture transmittance will attenuate and saturate with increasing Kerr constant. (C) 2003 Optical Society of America.

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A new theoretical model of Pattern Recognition principles was proposed, which is based on "matter cognition" instead of "matter classification" in traditional statistical Pattern Recognition. This new model is closer to the function of human being, rather than traditional statistical Pattern Recognition using "optimal separating" as its main principle. So the new model of Pattern Recognition is called the Biomimetic Pattern Recognition (BPR)(1). Its mathematical basis is placed on topological analysis of the sample set in the high dimensional feature space. Therefore, it is also called the Topological Pattern Recognition (TPR). The fundamental idea of this model is based on the fact of the continuity in the feature space of any one of the certain kinds of samples. We experimented with the Biomimetic Pattern Recognition (BPR) by using artificial neural networks, which act through covering the high dimensional geometrical distribution of the sample set in the feature space. Onmidirectionally cognitive tests were done on various kinds of animal and vehicle models of rather similar shapes. For the total 8800 tests, the correct recognition rate is 99.87%. The rejection rate is 0.13% and on the condition of zero error rates, the correct rate of BPR was much better than that of RBF-SVM.

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A novel accurate numerical model for shallow water equations on sphere have been developed by implementing the high order multi-moment constrained finite volume (MCV) method on the icosahedral geodesic grid. High order reconstructions are conducted cell-wisely by making use of the point values as the unknowns distributed within each triangular cell element. The time evolution equations to update the unknowns are derived from a set of constrained conditions for two types of moments, i.e. the point values on the cell boundary edges and the cell-integrated average. The numerical conservation is rigorously guaranteed. in the present model, all unknowns or computational variables are point values and no numerical quadrature is involved, which particularly benefits the computational accuracy and efficiency in handling the spherical geometry, such as coordinate transformation and curved surface. Numerical formulations of third and fourth order accuracy are presented in detail. The proposed numerical model has been validated by widely used benchmark tests and competitive results are obtained. The present numerical framework provides a promising and practical base for further development of atmospheric and oceanic general circulation models. (C) 2009 Elsevier Inc. All rights reserved.

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The properties of hadronic matter at beta equilibrium in a wide range of densities are described by appropriate equations of state in the framework of the relativistic mean field model. Strange meson fields, namely the scalar meson field sigma*(975) and the vector meson field sigma*(1020), are included in the present work. We discuss and compare the results of the equation of state, nucleon effective mass, and strangeness fraction obtained by adopting the TM1, TMA, and GL parameter sets for nuclear sector and three different choices for the hyperon couplings. We find that the parameter set TM1 favours the onset of hyperons most, while at high densities the GL parameter set leads to the most hyperon-rich matter. For a certain parameter set (e.g. TM1), the most hyperon-rich matter is obtained for the hyperon potential model. The influence of the hyperon couplings on the effective mass of nucleon, is much weaker than that on the nucleon parameter set. The nonstrange mesons dominate essentially the global properties of dense hyperon matter. The hyperon potential model predicts the lowest value of the neutron star maximum mass of about 1.45 M-sun to be 0.4-0.5 M-sun lower than the prediction by using the other choices for hyperon couplings.

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By using phi-mapping method, we discuss the topological structure of the self-duality solution in Jackiw-Pi model in terms of gauge potential decomposition. We set up relationship between Chern-Simons vortex solution and topological number, which is determined by Hopf index and Brouwer degree. We also give the quantization of flux in this case. Then, we study the angular momentum of the vortex, which can be expressed in terms of the flux.

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A set of bimetallic Pt-Ru catalysts prepared by co-impregnation of carbon black with ruthenium(III) chloride hydrate and hydrogen hexachloroplatinate(IV) hydrate were investigated by temperature-programmed reduction (TPR), chemisorption of hydrogen, transmission electron microscopy (TEM), microcalorimetry of adsorbed CO and a structure-sensitive reaction (n-hexane conversion). The results showed that the volumetric capacities for CO and H-2 adsorption is influenced in the bimetallic Pt-Ru catalysts by the formation of a Pt-Ru alloy. The n-hexane reaction revealed that the reaction mechanism for the pure Pt catalyst mainly occurs via cyclic isomerization and aromatization due to the presence of bigger Pt surface ensembles, whereas the Pt-Ru catalysts exhibited predominantly bond-shift isomerization by the diluting effect of Ru metal addition. The differential heats of CO chemisorption on Pt-Ru catalysts fell between the two monometallic Pt and Ru catalysts extremes. (C) 2004 Elsevier B.V. All rights reserved.

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This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt-and pepper-type noise. Second, considering the local geometrical features, e. g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method.

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The Gaussian process latent variable model (GP-LVM) has been identified to be an effective probabilistic approach for dimensionality reduction because it can obtain a low-dimensional manifold of a data set in an unsupervised fashion. Consequently, the GP-LVM is insufficient for supervised learning tasks (e. g., classification and regression) because it ignores the class label information for dimensionality reduction. In this paper, a supervised GP-LVM is developed for supervised learning tasks, and the maximum a posteriori algorithm is introduced to estimate positions of all samples in the latent variable space. We present experimental evidences suggesting that the supervised GP-LVM is able to use the class label information effectively, and thus, it outperforms the GP-LVM and the discriminative extension of the GP-LVM consistently. The comparison with some supervised classification methods, such as Gaussian process classification and support vector machines, is also given to illustrate the advantage of the proposed method.

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A coupled numerical model with a 2' x 2' resolution grid has been developed and used to simulate five typical typhoon storm surges (5612, 7413, 7910, 8114, and 9711) in the East Sea of China. Three main driving forces have been considered in this coupled model: wave radiation stress, combined wave-current bottom shear stress and wave-state-dependent surface wind stress. This model has then been compared with in situ measurements of the storm set-up. The effect of different driving force components on the total storm surge has also been investigated. This study has found that the coupled model with high resolution is capable of simulating the five typical typhoons better than the uncoupled models, and that the wave-dependent surface wind stress plays an important role in typhoon storm surge-wave coupling in this area and can increase the storm set-up by 1 m. The study of the five typhoon cases has shown that the general coupling effects could increase storm set-up by 20-32%. Thus, it is suggested that to predict typhoon storm surges in the East Sea of China, a storm surge-wave coupled model be adopted. (C) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

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A numerical adjoint model with TOPEX/POSEIDON (T/P) altimeter data was set up to investigate the shallow water tidal constituents in the Bohai Sea and the Yellow Sea. Shallow water tidal constituents W-4, MS4 and M-6) in the Bohai Sea and the Yellow Sea were first extracted from nearly 10 years of T/P data and then assimilated into a nonlinear barotropic tidal model by using adjoint method in order to fully describe the tides in this area. The general patterns of M-4 and MS4 solutions were in good agreement with those of Kang et al. (Cont. Shelf. Res. IS (1998) 739.) and Lefevre et al., (J. Geophys. Res. 105 (2000) 8707.). The RMS values for the principal constituents and coastal constituents were obviously less than those calculated by Kang et al. (1998) and Lefevre et al. (2000). It was shown that the calculated tidal constituents charts obtained in the present study were more accurate than those in other models. In the future the model will be applied to other coastal areas and some semi-enclosed seas. (C) 2004 Elsevier Ltd. All rights reserved.