Smoothed and Iterated Bootstrap Confidence Regions for Parameter Vectors

The construction of confidence regions for parameter vectors is a difficult problem in the nonparametric setting, particularly when the sample size is not large. The bootstrap has shown promise in solving this problem, but empirical evidence often indicates that some bootstrap methods have difficulty in maintaining the correct coverage probability, while other methods may be unstable, often resulting in very large confidence regions. One way to improve the performance of a bootstrap confidence region is to restrict the shape of the region in such a way that the error term of an expansion is as small an order as possible. To some extent, this can be achieved by using the bootstrap to construct an ellipsoidal confidence region. This paper studies the effect of using the smoothed and iterated bootstrap methods to construct an ellipsoidal confidence region for a parameter vector. The smoothed estimate is based on a multivariate kernel density estimator. This paper establishes a bandwidth matrix for the smoothed bootstrap procedure that reduces the asymptotic coverage error of the bootstrap percentile method ellipsoidal confidence region. We also provide an analytical adjustment to the nominal level to reduce the computational cost of the iterated bootstrap method. Simulations demonstrate that the methods can be successfully applied in practice

Annular flow pattern recognition using statistical data analyses of Electrical Impedance Tomography

Collecting very large amount of data from experimental multiphase measurement is a common practice in almost every scientific domain. There is a great need to have specific techniques capable of extracting synthetic information, which is essential to understand and model the specific flow phenomena. The intention of developing a method for recognition of flow regime using decomposition mathematical technique comes from the fact that each regime is characterised by typical dynamic behaviour. To recognise the flow dynamic structures, means indeed the recognition of the prevalent regime moreover indicates the actual flow conditions of the monitored area. The direct approach of Proper Orthogonal Decomposition (POD) as introduced by Lumley and the Linear Stochastic Estimation (LSE) as introduced by Adrian are used to identify typical multiphase flow instability. The present approach of statistical data-analysis extends the current evaluation procedure of Electrical Impedance Tomography (EIT) applied on air-water flow measurement. Wavelet Transformation and Kalman Filtering was used as complementary techniques for motion of fluid and flow structures detection and decomposed EIT signal similarity estimation. The paper demonstrates the capability of EIT measurement techniques combined with POD/LSE post-processing for studying annular flow patterns in vertical and horizontal pipeline

Numerical modelling of gas-liquid flow phenomena in horizontal pipelines

Gas-liquid flows are omnipresent in industrial and environmental processes. Examples are the transportation of petroleum products [1, 2], the cooling of nuclear reactors [3, 4], the operation of absorbers [5], distillation columns [6], gas lift pumps [7] and many mores. Different input parameters induce topologically different flow patterns with different flow character and behaviour [7, 8] . The present study concentrate to diabatic incompressible two-phase flow in horizontal pipeline with separated character [9, 10] (Ugas < 10m/s and Uliquid < 0:2m/s) such as stratified wavy flow regime including typical multiphase instability (Kelvin-elmholtz instability) [11, 12]. The Proper Orthogonal Decomposition (POD) [13], introduced by Lumpay (1967) [14] was used to extract synthetic information essential to understand and to model flow dynamics phenomena. POD in this study are used to identify flow structure in the horizontal pipeline specially under transient of separated flow regimes. The snapshot matrix are reconstruct for specific flow sections and regimes. Present decomposition method, in this case used to analyse CFD data, are originally testing and developing for future using to analyse experimental data obtained by process tomography system [15]

Proper Orthogonal Decomposition as a technique for identifying multiphase flow regime based on Electrical Impedance Tomography

Collecting very large amount of data from experimental measurement is a common practice in almost every scientific domain. There is a great need to have specific techniques capable of extracting synthetic information, which is essential to understand and model the specific phenomena. The Proper Orthogonal Decomposition (POD) is one of the most powerful data-analysis methods for multivariate and nonlinear phenomena. Generally, POD is a procedure that takes a given collection of input experimental or numerical data and creates an orthogonal basis constituted by functions estimated as the solutions of an integral eigenvalue problem known as a Fredholm equation. By utilising POD to identify flow structure in horizontal pipeline, specially, for slag, plug and wavy stratified air-water flow regimes, this paper proposes a novel approach, in which POD technique extends the current evaluation procedure of Electrical Impedance Tomography applied on air-water flow measurement. This extension is provided by implementation of the POD as an identifier of typical horizontal multiphase flow regimes. The POD snapshot matrices are reconstructed for EIT measurement domain and specific flow conditions. Direct POD method introduced by Lumley is applied. It is expected that this study may provide new knowledge on two phase flow dynamics in a horizontal pipeline and supportive information for further prediction of multiphase flow regime

Experimental Evaluation of Dual-Modality Electrical Tomographic Systems on Gas-Oil-Water Flow in Horizontal Pipeline

A variety of dual-modality tomographic systems have been proposed for the characterisation of multiphase flow, but the evaluation of such systems are generally carried out under simplified flow conditions, such as stratified flow and slug flow. This paper reports the evaluation results of a dualmodality electrical tomographic system in an industry-scale gas-oil-water three-phase flow. Experimental conditions include water-to-liquid ratio (WLR) from 0% to 100% in parallel with gas volume fractions from 0% to 100%, which produces a variety of flow patterns, such as stratified-wavy flow, slug flow, plug flow, bubbly flow, and annular flow. Commercialised ITS M3C (ECT) and V5R (ERT) dual-modality systems were applied to perform the measurement. A threshold-based multidimensional data fused approach was implemented for the data fusion process. The results demonstrated that the ERT system is able to measure water continuous flow with WLR higher than 40%, which is in good agreement with previous reports. The ECT system is able to measure from 0% to 100% WLR, far beyond its conventional capabilities. Even though the tomograms are distorted when WLR is higher than 90%, this result is much better than the reported 40% limit. Visualisation and mean concentration derived from the tomograms by advanced data fusion verify the capability of the system in the application of gas-oil-water flow characterisation

Coronary Risk Assessment by Point-Based vs. Equation-Based Framingham Models: Significant Implications for Clinical Care

US cholesterol guidelines use original and simplified versions of the Framingham model to estimate future coronary risk and thereby classify patients into risk groups with different treatment strategies. We sought to compare risk estimates and risk group classification generated by the original, complex Framingham model and the simplified, point-based version. We assessed 2,543 subjects age 20–79 from the 2001–2006 National Health and Nutrition Examination Surveys (NHANES) for whom Adult Treatment Panel III (ATP-III) guidelines recommend formal risk stratification. For each subject, we calculated the 10-year risk of major coronary events using the original and point-based Framingham models, and then compared differences in these risk estimates and whether these differences would place subjects into different ATP-III risk groups (&lt;10% risk, 10–20% risk, or &gt;20% risk). Using standard procedures, all analyses were adjusted for survey weights, clustering, and stratification to make our results nationally representative. Among 39 million eligible adults, the original Framingham model categorized 71% of subjects as having “moderate” risk (&lt;10% risk of a major coronary event in the next 10 years), 22% as having “moderately high” (10–20%) risk, and 7% as having “high” (&gt;20%) risk. Estimates of coronary risk by the original and point-based models often differed substantially. The point-based system classified 15% of adults (5.7 million) into different risk groups than the original model, with 10% (3.9 million) misclassified into higher risk groups and 5% (1.8 million) into lower risk groups, for a net impact of classifying 2.1 million adults into higher risk groups. These risk group misclassifications would impact guideline-recommended drug treatment strategies for 25–46% of affected subjects. Patterns of misclassifications varied significantly by gender, age, and underlying CHD risk. Compared to the original Framingham model, the point-based version misclassifies millions of Americans into risk groups for which guidelines recommend different treatment strategies

The Causal Structure of Emotions in Aristotle: Hylomorphism, Causal Interaction between Mind and Body, and Intentionality

Recently, a strong hylomorphic reading of Aristotelian emotions has been put forward, one that allegedly eliminates the problem of causal interaction between soul and body. Taking the presentation of emotions in de An. I 1 as a starting point and basic thread, but relying also on the discussion of Rh. II, I will argue that this reading only takes into account two of the four causes of emotions, and that, if all four of them are included into the picture, then a causal interaction of mind and body remains within Aristotelian emotions, independent of how strongly their hylomorphism is understood. Beyond the discussion with this recent reading, the analysis proposed of the fourfold causal structure of emotions is also intended as a hermeneutical starting point for a comprehensive analysis of particular emotions in Aristotle. Through the different causes Aristotle seems to account for many aspects of the complex phenomenon of emotion, including its physiological causes, its mental causes, and its intentional object