13,836 research outputs found
Uncertainty in 2-point correlation function estimators and BAO detection in SDSS DR7
We study the uncertainty in different two-point correlation function (2PCF)
estimators in currently available galaxy surveys. This is motivated by the
active subject of using the baryon acoustic oscillations (BAOs) feature in the
correlation function as a tool to constrain cosmological parameters, which
requires a fine analysis of the statistical significance. We discuss how
estimators are affected by both the uncertainty in the mean density
and the integral constraint
which necessarily causes a bias. We quantify both effects for currently
available galaxy samples using simulated mock catalogues of the Sloan Digital
Sky Survey (SDSS) following a lognormal model, with a Lambda-Cold Dark Matter
() correlation function and similar properties as the
samples (number density, mean redshift for the correlation
function, survey geometry, mass-luminosity bias). Because we need extensive
simulations to quantify small statistical effects, we cannot use realistic
N-body simulations and some physical effects are neglected. Our simulations
still enable a comparison of the different estimators by looking at their
biases and variances. We also test the reliability of the BAO detection in the
SDSS samples and study the compatibility of the data results with our
simulations.Comment: 14 pages, 6 figures, 3 table
On the robustness of the average power ratios in damping estimation: application in the structural health monitoring of composites beams
In composites structures, cracking, delamination will cause changes in the measured dynamic response of structure and so on experimentally modal parameters. Estimation of damping in structural control often poses a difficult problem especially using broadband experiments. If these estimations are faulty, it is difficult to propose a robust Structural Health Monitoring (SHM) algorithm. Recently H.P. Yin introduced the optimal power ratios damping estimator. A new theoretical basis of the bandwidth method for the damping estimation from frequency response functions (in case of a single degree of freedom system) has been proposed. The main goal of this paper is to study the robustness of this enhanced damping estimator on simulated signal (sampling frequency, Signal to Noise Ratio and damping level/density), and also compare its performance with industrial improved estimator like âPolymaxâ on experimental Frequency Response Functions (FRFs). The pole shifts would be studied as a change in the frequency-damping plane function of level and density of damage
Assessing forest availability for wood supply in Europe
The quantification of forests available for wood supply (FAWS) is essential for decision-making with regard to
the maintenance and enhancement of forest resources and their contribution to the global carbon cycle. The
provision of harmonized forest statistics is necessary for the development of forest associated policies and to
support decision-making. Based on the National Forest Inventory (NFI) data from 13 European countries, we
quantify and compare the areas and aboveground dry biomass (AGB) of FAWS and forest not available for wood
supply (FNAWS) according to national and reference definitions by determining the restrictions and associated
thresholds considered at country level to classify forests as FAWS or FNAWS.
FAWS represent between 75 and 95 % of forest area and AGB for most of the countries in this study. Economic
restrictions are the main factor limiting the availability of forests for wood supply, accounting for 67 % of the
total FNAWS area and 56 % of the total FNAWS AGB, followed by environmental restrictions. Profitability, slope
and accessibility as economic restrictions, and protected areas as environmental restrictions are the factors most
frequently considered to distinguish between FAWS and FNAWS. With respect to the area of FNAWS associated
with each type of restriction, an overlap among the restrictions of 13.7 % was identified. For most countries, the differences in the FNAWS areas and AGB estimates between national and reference definitions ranged from 0 to
5 %. These results highlight the applicability and reliability of a FAWS reference definition for most of the
European countries studied, thereby facilitating a consistent approach to assess forests available for supply for
the purpose of international reportinginfo:eu-repo/semantics/publishedVersio
Expansion Abroad and Jobs at Home - Evidence from Japanese Multinational Enterprises
This paper examines the exporting job hypothesis that expansion of overseas operations of manufacturing multinational enterprises (MNEs) reduces home employment using data for Japanese MNEs. While the existing studies are mainly based on the industry level data, this paper presents the evidence using a newly constructed firm-level panel data set over the period 1991-2002. The evidence does not support the widely-held view in Japanese policy circles that that overseas operations of MNEs expand at the cost of home employment. On the contrary, there is some evidence that overseas operations may have helped to maintain the level of home employment.Multinational Enterprises, FDI, labour demand, Globalisation
Bayesian spline method for assessing extreme loads on wind turbines
This study presents a Bayesian parametric model for the purpose of estimating
the extreme load on a wind turbine. The extreme load is the highest stress
level imposed on a turbine structure that the turbine would experience during
its service lifetime. A wind turbine should be designed to resist such a high
load to avoid catastrophic structural failures. To assess the extreme load,
turbine structural responses are evaluated by conducting field measurement
campaigns or performing aeroelastic simulation studies. In general, data
obtained in either case are not sufficient to represent various loading
responses under all possible weather conditions. An appropriate extrapolation
is necessary to characterize the structural loads in a turbine's service life.
This study devises a Bayesian spline method for this extrapolation purpose,
using load data collected in a period much shorter than a turbine's service
life. The spline method is applied to three sets of turbine's load response
data to estimate the corresponding extreme loads at the roots of the turbine
blades. Compared to the current industry practice, the spline method appears to
provide better extreme load assessment.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS670 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Keys to effective transit strategies for commuting
Commuting poses relevant challenges to cities\u2019 transport systems. Various studies have identified transit as a tool to enhance sustainability, efficiency and quality of the commute. The scope of this paper is to present strategies that increase public transport attractiveness and positively impact its modal share, looking at some case studies and underlining key success factors and possible elements of replica to be ultimately planned in some of the contexts of the Interreg project SMART-COMMUTING. The strategies analyzed in this paper concern prices and fares, service expansion, service improvements, usage of vehicle locators and other technology, changes to the built environment. Relevant gains in transit modal share are more easily achievable when considering integrations between various strategies, thus adapting and tailoring the planning process to the specific context
Methodological Issues in Spatial Microsimulation Modelling for Small Area Estimation
In this paper, some vital methodological issues of spatial microsimulation modelling for small area estimation have been addressed, with a particular emphasis given to the reweighting techniques. Most of the review articles in small area estimation have highlighted methodologies based on various statistical models and theories. However, spatial microsimulation modelling is emerging as a very useful alternative means of small area estimation. Our findings demonstrate that spatial microsimulation models are robust and have advantages over other type of models used for small area estimation. The technique uses different methodologies typically based on geographic models and various economic theories. In contrast to statistical model-based approaches, the spatial microsimulation model-based approaches can operate through reweighting techniques such as GREGWT and combinatorial optimization. A comparison between reweighting techniques reveals that they are using quite different iterative algorithms and that their properties also vary. The study also points out a new method for spatial microsimulation modellingBayesian prediction approach; combinatorial optimisation; GREGWT; microdata; small area estimation; spatial microsimulation
Data-driven through-life costing to support product lifecycle management solutions in innovative product development
Innovative product usually refers to product that comprises of creativity and new ideas. In the development of such a new product, there is often a lack of historical knowledge and data available to be used to perform cost estimation accurately. This is due to the fact that traditional cost estimation methods are used to predict costs only after a product model has been built, and not at an early design stage when there is little data and information available.
In light of this, original equipment manufacturers are also facing critical challenges of becoming globally competitive and increasing demands from customer for continuous innovation. To alleviate these situations this research has identified a new approach to cost modelling with the inclusion of product lifecycle management solutions to address innovative product development.The aim of this paper, therefore, is to discuss methods of developing an extended-enterprise data-driven through-life cost estimating method for innovative product development
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