Energy harvesting in a Mathieu–van der Pol–Duffing MEMS device using time delay

This paper investigates quasi-periodic vibration-based energy harvesting in a delayed nonlinear MEMS device consisting of a delayed Mathieu–van der Pol–Duffing type oscillator coupled to a delayed piezoelectric coupling mechanism. We use the multiple scales method to approximate the quasi-periodic response and the related power output near the principal parametric resonance. The effect of time delay on the energy harvesting performance is studied. It is shown that for appropriate combination of time delay parameters, there exists an optimum range of excitation frequency beyond the resonance where quasi-periodic vibration-based energy harvesting is maximum. Numerical simulations are performed to confirm the analytical predictions.     

Multi-scale Modeling of Vision-Guided Remodeling and Age-Dependent Growth of the Tree Shrew Sclera During Eye Development and Lens-Induced Myopia

The sclera uses unknown mechanisms to match the eye’s axial length to its optics during development, producing eyes with good focus (emmetropia). A myopic eye is too long for its own optics. We propose a multi-scale computational model to simulate eye development based on the assumption that scleral growth is controlled by genetic factors while scleral remodeling is driven by genetic factors and the eye’s refractive error. We define growth as a mechanism that changes the tissue volume and mass while remodeling involves internal micro-deformations that are volume-preserving at the macro-scale. The model was fitted against longitudinal refractive measurements in tree shrews of different ages and exposed to three different visual conditions: (i) normal development; (ii) negative lens wear to induce myopia; and (iii) recovery from myopia by removing the negative lens. The model was able to replicate the age- and vision-dependent response of the tree shrew experiments. Scleral growth ceased at younger age than scleral remodeling. The remodeling rate decreased as the eye emmetropized but increased at any age when a negative lens was put on. The predictive power of the model was investigated by calculating the susceptibility to scleral remodeling and the response to form deprivation myopia in tree shrews. Both predictions were in good agreement with experimental data that were not used to fit the model. We propose the first model that distinguishes scleral growth from remodeling. The good agreement of our results with experimental data supports the notion that scleral growth and scleral remodeling are two independently controlled mechanisms during eye development.     

Numerical solution for a sub-diffusion equation with a smooth kernel

In this paper we study the numerical solution of an initial value problem of a sub-diffusion type. For the time discretization we apply the discontinuous Galerkin method and we use continuous piecewise finite elements for the space discretization. Optimal order convergence rates of our numerical solution have been shown. We compare our theoretical error bounds with the results of numerical computations. We also present some numerical results showing the super-convergence rates of the proposed method.     

Evaluation of bit error rate for packet combining with constellation rearrangement

In this paper, we propose a method for evaluation of the bit error rate (BER) for packet combining based on constellation rearrangement (CoRe). Such mapping diversity scheme, adopted in the high speed downlink packet access (HSDPA), uses Gray‐mapped constellations and is based on suboptimal accumulation of the reliability metrics generated in each of the transmissions. We present an exact model for the logarithmic likelihood ratios (LLR) obtained by means of the so‐called max‐log approximation, and we show that their conditional probability density functions (pdf) are piecewise Gaussian. We then present the derivation of the uncoded BER and illustrate it with simulation results that confirm our formulation. Finally, we propose simplifications which significantly reduce the complexity of the evaluation method and provide results with a very good accuracy; an extension to transmissions over faded channel is also presented. Copyright © 2007 John Wiley & Sons, Ltd.     

Spin versus helicity: Processes involving transversity

We construct the spin formalism in order to deal naturally with processes involving transversity which are now of increasing popularity. The helicity formalism which is more appropriate for collision processes of definite helicity has been so far used to also manage processes with transversity, but at the price of computing numerous helicity amplitudes which generally involve unnecessary kinematical variables.     

Mapping of muscle deformation during heating: in situ dynamic MRI and nonlinear registration

We present developments in dynamic magnetic resonance imaging that allow internal structural muscle markers to be followed during heating. This monitoring is based on quantitative characterization of the experimental conditions and their temperature time course. A nonlinear image registration technique was optimized and applied to consecutively acquired images to measure the deformation fields in the muscle. A model coupling local deformation and temperature was obtained, which for the first time takes into account the variations of deformation and temperature in the sample. This modeling opens the way to a better understanding of the mechanisms responsible for mass loss and degradation of the textural properties of muscle during heating.     

A novel fuzzy C-means algorithm to generate diverse and desirable cluster solutions used by genetic-based clustering ensemble algorithms

One of the most significant discussions in the field of machine learning today is on the clustering ensemble. The clustering ensemble combines multiple partitions generated by different clustering algorithms into a single clustering solution. Genetic algorithms are known for their high ability to solve optimization problems, especially the problem of the clustering ensemble. To date, despite the major contributions to find consensus cluster partitions with application of genetic algorithms, there has been little discussion on population initialization through generative mechanisms in genetic-based clustering ensemble algorithms as well as the production of cluster partitions with favorable fitness values in first phase clustering ensembles. In this paper, a threshold fuzzy C-means algorithm, named TFCM, is proposed to solve the problem of diversity of clustering, one of the most common problems in clustering ensembles. Moreover, TFCM is able to increase the fitness of cluster partitions, such that it improves performance of genetic-based clustering ensemble algorithms. The fitness average of cluster partitions generated by TFCM are evaluated by three different objective functions and compared against other clustering algorithms. In this paper, a simple genetic-based clustering ensemble algorithm, named SGCE, is proposed, in which cluster partitions generated by the TFCM and other clustering algorithms are used as the initial population used by the SGCE. The performance of the SGCE is evaluated and compared based on the different initial populations used. The experimental results based on eleven real world datasets demonstrate that TFCM improves the fitness of cluster partitions and that the performance of the SGCE is enhanced using initial populations generated by the TFCM.     

Finite dynamic deformations of a hyperelastic,anisotropic, incompressible and prestressed tube. Applications to in vivo arteries

In this paper, we study the mechanical behavior of a prestressed tube subjected to finite dynamic deformations. The tube is assumed to be made of a hyperelastic, anisotropic and incompressible material. The analysis is carried out by using a Mooney–Rivlin stored energy function augmented with fiber reinforcements in four unidimensional orientations. A semi-analytical solution is proposed to study the radial dynamic mechanical response of an artery by using in vivo data. The optimal model parameters describing the mechanical characteristics of arterial wall microconstituents are obtained by minimizing the difference between computed and measured inner pressures over the cardiac cycle using a nonlinear regression. Theoretical and experimental results on rat carotid elastic arteries are compared in order to assess the validity of the approach by estimating differences of the model parameters and wall stresses with aging.     

Reducing Test Time in the High-Volume Production of Analog Circuits using Efficient Test-Vector Generation and Interpolation Techniques

Test cost is one of the main factors determining the profit margin of a device in production. Current test strategies require hundreds of measurements to determine the specifications of a parameter. In this paper, we present an automatic test-vector generation technique that is based on transfer function manipulation and requires only one circuit simulation. The proposed method consists of generating the first set of vectors by applying a derivation technique to the golden transfer function of the circuit under test (CUT). An interpolation technique allows a new transfer function to be constructed based on the first set of test vectors. The difference between the reconstructed transfer function and the golden transfer function is used to select the second set of test vectors. These new test vectors are selected to achieve the best possible fit. Our technique reduces the test vector size to values that at present can be achieved only by using powerful and time-consuming fault simulation tools. As an example, we apply the method to state variable and Chebyshev filters. We also compute the fault coverage in order to demonstrate the effectiveness of this new technique.