Bootstrapping to choose an estimator after sampling on two occasions

Email: a.brint{at}sheffield.ac.uk Received on 22 August 2007. Accepted on 13 June 2008. When successive surveys are undertaken so as to keep a populationestimate up to date, combining the data from the most recentsurvey with data from earlier surveys is more efficient thanjust using the most recent survey. The standard approach tocombining the data forms separate estimates from the set ofitems observed on the earlier occasion and the set observedon the later occasion and then forms a combined estimate. Theapproach assumes that the population is very large and thatthe observed values of the variable of interest are continuous.In many situations, neither assumption is particularly appropriate.This paper compares an alternative approach with the standardapproach and finds that the alternative approach sometimes providesa better estimator. It then puts forward an improved estimatorbased on choosing between these approaches using a bootstrapprocedure.     

Multiple pathways in conformational transitions of the alanine dipeptide: an application of dynamic importance sampling

We present multiple dynamic transition pathways on the two-dimensional dihedral plane between conformational states of the alanine dipeptide. The method used in this study is dynamic importance sampling (DIMS). To perform DIMS, unbiased molecular dynamic simulations are used to generate equilibrium ensembles for the alanine dipeptide within different states. Free energy surfaces on the dihedral plane are calculated from the equilibrium simulations, and four energy minima defined from the surface are used as the starting and ending points for DIMS dynamics. The DIMS method represents an important step towards finding multiple transition pathways within complex biomolecular systems.     

Thermodynamic properties of Ag2O--B2O3 glasses by a modified scale-transformed energy space sampling Monte Carlo method

The density of states of Ag(2)O--B(2)O(3) glasses has been calculated by using a modified scale-transformed energy space sampling algorithm. This algorithm combines the scale-transformed energy space sampling algorithm and the Wang-Landau method. It is shown how the two algorithms can be combined to improve the efficiency of calculation. The thermodynamic properties, in particular the specific heat C(V), of the above-mentioned glass system is studied. At temperatures above 80 K, the value of specific heat C(v) is close to 22 J/mol/K. At low temperatures, the deviations of C(v) from a T(3) behavior are discernible, that is, C(v)/T(3) exhibits a hump at T = 7 K, which is in good agreement with the reported experimental behavior.     

Free-form deformation,mesh morphing and reduced-order methods: enablers for efficient aerodynamic shape optimisation

ABSTRACT

In this work, we provide an integrated pipeline for the model-order reduction of turbulent flows around parametrised geometries in aerodynamics. In particular, free-form deformation is applied for geometry parametrisation, whereas two different reduced-order models based on proper orthogonal decomposition (POD) are employed in order to speed-up the full-order simulations: the first method exploits POD with interpolation, while the second one is based on domain decomposition. For the sampling of the parameter space, we adopt a Greedy strategy coupled with Constrained Centroidal Voronoi Tessellations, in order to guarantee a good compromise between space exploration and exploitation. The proposed framework is tested on an industrially relevant application, i.e. the front-bumper morphing of the DrivAer car model, using the finite-volume method for the full-order resolution of the Reynolds-Averaged Navier–Stokes equations.     

Adaptive Feedback Stabilization with Quantized State Measurements for a Class of Chaotic Systems

We investigate asymptotical stabilization for a class of chaotic systems by means of quantization measurements of states. The quantizer adopted in this paper takes finite many values. In particular, one zoomer is placed at the input terminal of the quantizer, and another zoomer is located at the output terminal of the quantizer. The zoomers possess a common adjustable time-varying parameter. By using the adaptive laws for the time-varying parameter and estimating boundary error of values of quantization, the stabilization feedback controller with the quantized state measurements is proposed for a class of chaotic systems. Finally, some numerical examples are given to demonstrate the validity of the proposed methods.     

Microcanonical Phase Diagram of the BEG and Ising Models

The density of states of long-range Blume-Emery-Griffiths (BEG) and short-range Ising models are obtained by using Wang-Landau sampling with adaptive windows in energy and magnetization space. With accurate density of states, we are able to calculate the microcanonical specific heat of fixed magnetization introduced by Kastner et al. in the regions of positive and negative temperature. The microcanonical phase diagram of the Ising model shows a continuous phase transition at a negative temperature in energy and magnetization plane. However the phase diagram of the long-range model constructed by peaks of the microcanonical specific heat looks obviously different from the Ising chart.     

Massively parallel mesh adaptation and linear system solution for multiphase flows

ABSTRACT

In this paper, a work performed to allow massively parallel finite element flow computations is presented. It includes the development and optimisation of two particular features of a finite element multiphase computational fluid dynamics software, which are mesh generation and linear system solution, using anisotropic adaptation and multigrid preconditioning. Parallel performances on supercomputers are shown, where the largest generated mesh (on 65 536 Intel Xeon or 261 144 Power PC cores) had 33.4 billions of nodes, leading to a 100 billion of unknowns linear system solution. Final applications concern, between others, image-based flow simulations.     

Uncertainty evaluation of continuous noise sampling

An area of current interest and topic of multiple publications is the assessment of uncertainty in estimating long-term indicators from measurements made for periods of time of less than 1 year. In this work, these prior investigations have been used as a starting point.Based on measurements made during one whole year at 26 sampling points with variables of urban and traffic characteristics, it was considered two aims related to uncertainty in the estimation of the annual L_den. The strength of this study is the large amount of data, which allows to simulate real measurements by sampling data from random days. Thus, it was studied in detail the predictive ability of the expressions proposed in the literature. Associated with this objective, then it was sought to evaluate the uncertainty associated with the estimation of annual L_den when random days of sampling were much lower than a full year.The results indicate the need for further progress in the theoretical determination of uncertainty. Second, the results made it able to estimate the uncertainty for the L_den indicator based on the number days sampled randomly.     

Linear quantification calibration of crystallinity at subpercent and its evaluation based on spectral and spatial information inherited in Raman chemical images

In this paper, the author reported two methods to extract spectral or spatial information inherited in the Raman chemical images for linear quantification calibration of crystallinity. The two approaches reported quantification results according to the spectral mean score of overall pixels or the spatial percentage of the pixels with a score greater than and equal to the threshold of the chemical images, respectively. From this study, it can be concluded that, first, sampling method for data collection in mapping has to be optimized to achieve linear quantification calibration through simple univariate analysis approaches. Second, the ordinary way of evaluating/validating a linear quantification technique by best linear correlation coefficient (R²) and root‐mean‐square error of calibration is disputable and has to be reconsidered. Lastly, with further consideration of root‐mean‐square relative error of calibration and predicted crystallinity at subpercent, it was found that the spectral mean score method cannot generate reliable quantification results at subpercent crystallinity. Copyright © 2014 John Wiley & Sons, Ltd.     

Evolutionary model of the growth and size of firms

The key idea of this model is that firms are the result of an evolutionary process. Based on demand and supply considerations the evolutionary model presented here derives explicitly Gibrat’s law of proportionate effects as the result of the competition between products. Applying a preferential attachment mechanism for firms, the theory allows to establish the size distribution of products and firms. Also established are the growth rate and price distribution of consumer goods. Taking into account the characteristic property of human activities to occur in bursts, the model allows also an explanation of the size–variance relationship of the growth rate distribution of products and firms. Further the product life cycle, the learning (experience) curve and the market size in terms of the mean number of firms that can survive in a market are derived. The model also suggests the existence of an invariant of a market as the ratio of total profit to total revenue. The relationship between a neo-classic and an evolutionary view of a market is discussed. The comparison with empirical investigations suggests that the theory is able to describe the main stylized facts concerning the size and growth of firms.