Direct dynamical test for deterministic chaos and optimal embedding of a chaotic time-series

We propose here a local exponential divergence plot which is capable of providing an alternative means of characterizing a complex time series. The suggested plot defines a time-dependent exponent and a ''plus'' exponent. Based on their changes with the embedding dimension and delay time, a criterion for estimating simultaneously the minimal acceptable embedding dimension, the proper delay time, and the largest Lyapunov exponent has been obtained. When redefining the time-dependent exponent LAMBDA(k) curves on a series of shells, we have found that whether a linear envelope to the LAMBDA(k) curves exists can serve as a direct dynamical method of distinguishing chaos from noise.

Local exponential divergence plot and optimal embedding of a chaotic time-series

we propose here a local exponential divergence plot which is capable of providing a new means of characterizing chaotic time series. The suggested plot defines a time dependent exponent LAMBDA and a ''plus'' exponent LAMBDA+ which serves as a criterion for estimating simultaneously the minimal acceptable embedding dimension, the proper delay time and the largest Lyapunov exponent.

Partially Supervised Neighbor Embedding for Example-Based Image Super-Resolution

Neighbor embedding algorithm has been widely used in example-based super-resolution reconstruction from a single frame, which makes the assumption that neighbor patches embedded are contained in a single manifold. However, it is not always true for complicated texture structure. In this paper, we believe that textures may be contained in multiple manifolds, corresponding to classes. Under this assumption, we present a novel example-based image super-resolution reconstruction algorithm with clustering and supervised neighbor embedding (CSNE). First, a class predictor for low-resolution (LR) patches is learnt by an unsupervised Gaussian mixture model. Then by utilizing class label information of each patch, a supervised neighbor embedding is used to estimate high-resolution (HR) patches corresponding to LR patches. The experimental results show that the proposed method can achieve a better recovery of LR comparing with other simple schemes using neighbor embedding.

A Study of Composite Beam with Shape Memory Alloy Arbitrarily Embedded under Thermal and Mechanical Loadings

The constitutive relations and kinematic assumptions on the composite beam with shape memory alloy (SMA) arbitrarily embedded are discussed and the results related to the different kinematic assumptions are compared. As the approach of mechanics of materials is to study the composite beam with the SMA layer embedded, the kinematic assumption is vital. In this paper, we systematically study the kinematic assumptions influence on the composite beam deflection and vibration characteristics. Based on the different kinematic assumptions, the equations of equilibrium/motion are different. Here three widely used kinematic assumptions are presented and the equations of equilibrium/motion are derived accordingly. As the three kinematic assumptions change from the simple to the complex one, the governing equations evolve from the linear to the nonlinear ones. For the nonlinear equations of equilibrium, the numerical solution is obtained by using Galerkin discretization method and Newton-Rhapson iteration method. The analysis on the numerical difficulty of using Galerkin method on the post-buckling analysis is presented. For the post-buckling analysis, finite element method is applied to avoid the difficulty due to the singularity occurred in Galerkin method. The natural frequencies of the composite beam with the nonlinear governing equation, which are obtained by directly linearizing the equations and locally linearizing the equations around each equilibrium, are compared. The influences of the SMA layer thickness and the shift from neutral axis on the deflection, buckling and post-buckling are also investigated. This paper presents a very general way to treat thermo-mechanical properties of the composite beam with SMA arbitrarily embedded. The governing equations for each kinematic assumption consist of a third order and a fourth order differential equation with a total of seven boundary conditions. Some previous studies on the SMA layer either ignore the thermal constraint effect or implicitly assume that the SMA is symmetrically embedded. The composite beam with the SMA layer asymmetrically embedded is studied here, in which symmetric embedding is a special case. Based on the different kinematic assumptions, the results are different depending on the deflection magnitude because of the nonlinear hardening effect due to the (large) deflection. And this difference is systematically compared for both the deflection and the natural frequencies. For simple kinematic assumption, the governing equations are linear and analytical solution is available. But as the deflection increases to the large magnitude, the simple kinematic assumption does not really reflect the structural deflection and the complex one must be used. During the systematic comparison of computational results due to the different kinematic assumptions, the application range of the simple kinematic assumption is also evaluated. Besides the equilibrium study of the composite laminate with SMA embedded, the buckling, post-buckling, free and forced vibrations of the composite beam with the different configurations are also studied and compared.

Component Assembling Model and Its Application to Quasi-Brittle Damage

Potential energy can be approximated by ‘‘pair-functional’’ potentials which is composed of pair potentials and embedding energy. Pair potentials are grouped according to discrete directions of atomic bonds such that each group is represented by an orientational component. Meanwhile, another kind of component, the volumetric one is derived from embedding energy. Damage and fracture are the changing and breaking of atomic bonds at the most fundamental level and have been reflected by the changing of these components’ properties. Therefore, material is treated as a component assembly, and its constitutive equations are formed by means of assembling these two kinds of components’ response functions. This material model is referred to as the component assembling model. Theoretical analysis and numerical computing indicate that the proposed model has the capacity of reproducing some results satisfactorily, with the advantages of physical explicitness and intrinsic induced anisotropy, etc.

Validation of component assembly model and extension to plasticity

Material potential energy is well approximated by '' pair-functional '' potentials. During calculating potential energy, the orientational and volumetric components have been derived from pair potentials and embedding energy, respectively. Slip results in plastic deformation, and slip component has been proposed accordingly. Material is treated as a component assembly, and its elastic, plastic and damage properties are reflected by different components respectively. Material constitutive relations are formed by means of assembling these three kinds of components. Anisotropy has been incorporated intrinsically via the concept of component. Theoretical and numerical results indicate that this method has the capacity of reproducing some results satisfactorily, with the advantages of physical explicitness, etc. (c) 2007 Elsevier Ltd. All rights reserved.

Influence of secondary void damage in the matrix material around voids

The mechanism of ductile damage caused by secondary void damage in the matrix around primary voids is studied by large strain, finite element analysis. A cylinder embedding an initially spherical void, a plane stress cell with a circular void and plane strain cell with a cylindrical or a flat void are analysed under different loading conditions. Secondary voids of smaller scale size nucleate in the strain hardening matrix, according to the requirements of some stress/strain criteria. Their growth and coalescence, handled by the empty element technique, demonstrate distinct mechanisms of damage as circumstances change. The macroscopic stress-strain curves are decomposed and illustrated in the form of the deviatoric and the volumetric parts. Concerning the stress response and the void growth prediction, comparisons are made between the present numerical results and those of previous authors. It is shown that loading condition, void growth history and void shape effect incorporated with the interaction between two generations of voids should be accounted for besides the void volume fraction.

The elasto-damage theory of the components assembling model

The potential energy in materials is well approximated by pair functional which is composed of pair potentials and embedding energy. During calculating material potential energy, the orientational component and the volumetric component are derived respectively from pair potentials and embedding energy. The sum of energy of all these two kinds of components is the material potential. No matter how microstructures change, damage or fracture, at the most level, they are all the changing and breaking atomic bonds. As an abstract of atomic bonds, these components change their stiffness during damaging. Material constitutive equations have been formulated by means of assembling all components' response functions. This material model is called the component assembling model. Theoretical analysis and numerical computing indicate that the proposed model has the capacity of reproducing some results satisfactorily, with the advantages of great conceptual simplicity, physical explicitness, and intrinsic induced anisotropy, etc.

Fabrication of two-dimensional periodic nanostructures by two-beam interference of femtosecond pulses

Two-dimensional periodic nanostructures on ZnO crystal surface were fabricated by two-beam interference of 790 nm femtosecond laser. The long period is, as usually reported, determined by the interference pattern of two laser beams. Surprisingly, there is another short periodic nanostructures with periods of 220-270 nm embedding in the long periodic structures. We studied the periods, orientation, and the evolution of the short periodic nanostructures, and found them analogous to the self-organized nanostructures induced by single fs laser beam. (C) 2008 Optical Society of America.

Au@Si-n: Growth behavior, stability and electronic structure

The configurations, stability, and electronic structure of AuSin (n = 1-16) clusters have been investigated within the framework of the density functional theory at the B3PW91/LanL2DZ and PW91/DNP levels. The results show that the Au atom begins to occupy the interior site for cages as small as Si-11 and for Si-12 the Au atom completely falls into the interior site forming Au@Si-12 cage. A relatively large embedding energy and small HOMO-LUMO gap are also found for this Au@Si-12 structure indicating enhanced chemical activity and good electronic transfer properties. All these make Au@Si-12 attractive for cluster-assembled materials.

Optical characteristics of InAs quantum dots on GaAs matrix by using various InGaAs structures

The effects of various InGaAs layers on the structural and optical properties of InAs self-assembled quantum dots (QDs) grown by molecular-beam epitaxy ( MBE) were investigated. The emission wavelength of 1317 nm was obtained by embedding InAs QDs in InGAs/GgAs quantum well. The temperature-dependent and timed-resolved photoluminescence (TDPL and TRPL) were used to study the dynamic characteristics of carriers. InGaAs cap layer may improve the quality of quantum dots for the strain relaxation around QDs, which results in a stronger PL intensity and an increase of PL peak lifetime up to 170 K. We found that InGaAs buffer layer may reduce the PL peak lifetime of InAs QDs, which is due to the buffer layer accelerating the carrier migration. The results also show that InGaAs cap layer can increase the temperature point when, the thermal reemission and nonradiative recombination contribute significantly to the carrier dynamics.

Phase character of the electron transport through a double quantum dot in a mesoscopic ring

We theoretically study the electron transport through a double quantum dot (QD) in the Coulomb blockade regime and reveal the phase character of the transport by embedding the double QD in a mesoscopic Aharonov-Bohm ring. It is shown that coherent transport through the double QD is preserved in spite of intradot and interdot Coulomb interactions.

Local histogram based geometric invariant image watermarking

Compared with other existing methods, the feature point-based image watermarking schemes can resist to global geometric attacks and local geometric attacks, especially cropping and random bending attacks (RBAs), by binding watermark synchronization with salient image characteristics. However, the watermark detection rate remains low in the current feature point-based watermarking schemes. The main reason is that both of feature point extraction and watermark embedding are more or less related to the pixel position, which is seriously distorted by the interpolation error and the shift problem during geometric attacks. In view of these facts, this paper proposes a geometrically robust image watermarking scheme based on local histogram. Our scheme mainly consists of three components: (1) feature points extraction and local circular regions (LCRs) construction are conducted by using Harris-Laplace detector; (2) a mechanism of grapy theoretical clustering-based feature selection is used to choose a set of non-overlapped LCRs, then geometrically invariant LCRs are completely formed through dominant orientation normalization; and (3) the histogram and mean statistically independent of the pixel position are calculated over the selected LCRs and utilized to embed watermarks. Experimental results demonstrate that the proposed scheme can provide sufficient robustness against geometric attacks as well as common image processing operations. (C) 2010 Elsevier B.V. All rights reserved.

Discriminative Orthogonal Neighborhood-Preserving Projections for Classification

Orthogonal neighborhood-preserving projection (ONPP) is a recently developed orthogonal linear algorithm for overcoming the out-of-sample problem existing in the well-known manifold learning algorithm, i.e., locally linear embedding. It has been shown that ONPP is a strong analyzer of high-dimensional data. However, when applied to classification problems in a supervised setting, ONPP only focuses on the intraclass geometrical information while ignores the interaction of samples from different classes. To enhance the performance of ONPP in classification, a new algorithm termed discriminative ONPP (DONPP) is proposed in this paper. DONPP 1) takes into account both intraclass and interclass geometries; 2) considers the neighborhood information of interclass relationships; and 3) follows the orthogonality property of ONPP. Furthermore, DONPP is extended to the semisupervised case, i.e., semisupervised DONPP (SDONPP). This uses unlabeled samples to improve the classification accuracy of the original DONPP. Empirical studies demonstrate the effectiveness of both DONPP and SDONPP.