Comparison of the polynomial model against explicit measurements of noise components for different mammography systems.

Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 µGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed.Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure.

Transfer of knowledge of the structural components of the model Q400 and Global Express: the case of Aerospace Bombardier, Querétaro

The aim of this paper is to analyze the knowledge transfer in the production of structural components of two aircraft:Q400 and Global Express of Bombardier Aerospace Company, Querétaro. Bombardier Aerospace is a pioneer company in the aviation sector in Mexico, and the third largest civil aircraft manufacturer. In 2005, Bombardier decided to invest in Mexico, creating Bombardier Aerospace de Mexico S. A. C. V. and transferring production lines from Japan and Toronto to Queretaro. The relocation strategy of both plants aims to reduce modular and general production costs facing other competitors. The relocation has been supported by the State Government funds, through a trust and the creation of Queretaro aerospace cluster. Among various benefits, the State of Queretaro donated seventy-eight acres of land where the Queretaro International Airport (QIA) and a training centre will be built to promote the development of this sector. The interest in this research is to analyze and describe the transfer of knowledge to the production of structural components of both aircraft models, thanks to the results of productivity and internal and external factors which have contributed along with this transfer

A comparison of three different models for estimating relative risk in meta-analysis of clinical trials under unobserved heterogeneity

We focus on the comparison of three statistical models used to estimate the treatment effect in metaanalysis when individually pooled data are available. The models are two conventional models, namely a multi-level and a model based upon an approximate likelihood, and a newly developed model, the profile likelihood model which might be viewed as an extension of the Mantel-Haenszel approach. To exemplify these methods, we use results from a meta-analysis of 22 trials to prevent respiratory tract infections. We show that by using the multi-level approach, in the case of baseline heterogeneity, the number of clusters or components is considerably over-estimated. The approximate and profile likelihood method showed nearly the same pattern for the treatment effect distribution. To provide more evidence two simulation studies are accomplished. The profile likelihood can be considered as a clear alternative to the approximate likelihood model. In the case of strong baseline heterogeneity, the profile likelihood method shows superior behaviour when compared with the multi-level model. Copyright (C) 2006 John Wiley & Sons, Ltd.

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed.

Validation of the Deardorff model for estimating energy balance components for a sugarcane crop

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Long- and medium-range components of the nuclear force in quark-model based calculations

Quark-model descriptions of the nucleon-nucleon interaction contain two main ingredients, a quark-exchange mechanism for the short-range repulsion and meson exchanges for the medium- and long-range parts of the interaction. We point out the special role played by higher partial waves, and in particular the (1)F(3), as a very sensitive probe for the meson-exchange pan employed in these interaction models. In particular, we show that the presently available models fail to provide a reasonable description of higher partial waves and indicate the reasons for this shortcoming.

A model for computing vibration induced stresses of electronic components in a general flexible mounting

This paper develops a novel full analytic model for vibration analysis of solid-state electronic components. The model is just as accurate as finite element models and numerically light enough to permit for quick design trade-offs and statistical analysis. The paper shows the development of the model, comparison to finite elements and an application to a common engineering problem. A gull-wing flat pack component was selected as the benchmark test case, although the presented methodology is applicable to a wide range of component packages. Results showed very good agreement between the presented method and finite elements and demonstrated the usefulness of the method in how to use standard test data for a general application. © 2013 Elsevier Ltd.

Expression of cellular components in granulomatous inflammatory response in piaractus mesopotamicus model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

Simulation tools for statistical model comparison: an application to unobserved componenet models versus dynamic regression models

Aplicación de simulación de Monte Carlo y técnicas de Análisis de la Varianza (ANOVA) a la comparación de modelos estocásticos dinámicos para accidentes de tráfico.

Hand receipt manual covering end item/components of end item (COEI), basic issue items (BII), and additional authorization list (AAL) related to compressor, reciprocating, air, receiver, mounted, electric motor driven, 5 cfm, 175 psi (Champion Pneumatic model 60CAW20HM-1) (national stock no. 4310-00-930-7147) ...

"February 1979."

Hand receipt covering contents of components of end item (COEI), basic issue items (BII), and additional authorization list (AAL) for tractor, full tracked, low speed, diesel engine-driven-medium-drawbar-pull : model, tractor with ripper ... NSN, 2410-01-223-0350 ....

"November 1992."

Hand receipt covering contents of components of end item (COEI), basic issue items (BII), and additional authorization list (AAL) for laundry unit, trailer mounted, model M85, NSN 3510-01-222-9301.

"17 June 1988."