Nonparametric Estimation of Data Dimensionality Prior to Data Compression: the case of the Human Development Index

In many applications in applied statistics researchers reduce the complexity of a data set by combining a group of variables into a single measure using factor analysis or an index number. We argue that such compression loses information if the data actually has high dimensionality. We advocate the use of a non-parametric estimator, commonly used in physics (the Takens estimator), to estimate the correlation dimension of the data prior to compression. The advantage of this approach over traditional linear data compression approaches is that the data does not have to be linearized. Applying our ideas to the United Nations Human Development Index we find that the four variables that are used in its construction have dimension three and the index loses information.

Spatial allocation of material flow analysis in residential developments: a case study of Kildare County, Ireland

Studies of urban metabolism provide important insights for environmental management of cities, but are not widely used in planning practice due to a mismatch of data scale and coverage. This paper introduces the Spatial Allocation of Material Flow Analysis (SAMFA) model as a potential decision support tool aimed as a contribution to overcome some of these difficulties and describes its pilot use at the county level in the Republic of Ireland. The results suggest that SAMFA is capable of identifying hotspots of higher material and energy use to support targeted planning initiatives, while its ability to visualise different policy scenarios supports more effective multi-stakeholder engagement. The paper evaluates this pilot use and sets out how this model can act as an analytical platform for the industrial ecology–spatial planning nexus.

On the use of OpenFOAM to model Oscillating wave surge converters

The Computational Fluid Dynamic (CFD) toolbox OpenFOAM is used to assess the applicability of Reynolds-Averaged Navier-Stokes (RANS) solvers to the simulation of Oscillating Wave Surge Converters (OWSC) in significant waves. Simulation of these flap type devices requires the solution of the equations of motion and the representation of the OWSC’s motion in a moving mesh. A new way to simulate the sea floor inside a section of the moving mesh with a moving dissipation zone is presented. To assess the accuracy of the new solver, experiments are conducted in regular and irregular wave traces for a full three dimensional model. Results of acceleration and flow features are presented for numerical and experimental data. It is found that the new numerical model reproduces experimental results within the bounds of experimental accuracy.

An Evaluation of 1D Loss Model Collections for the Off-Design Performance Prediction of an Automotive Turbocharger Compressor

Abstract. Single-zone modelling is used to assess different collections of impeller 1D loss models. Three collections of loss models have been identified in literature, and the background to each of these collections is discussed. Each collection is evaluated using three modern automotive turbocharger style centrifugal compressors; comparisons of performance for each of the collections are made. An empirical data set taken from standard hot gas stand tests for each turbocharger is used as a baseline for comparison. Compressor range is predicted in this study; impeller diffusion ratio is shown to be a useful method of predicting compressor surge in 1D, and choke is predicted using basic compressible flow theory. The compressor designer can use this as a guide to identify the most compatible collection of losses for turbocharger compressor design applications. The analysis indicates the most appropriate collection for the design of automotive turbocharger centrifugal compressors.

The effects of blood pressure lowering on development of cognitive impairment and dementia in patients without apparent prior cerebrovascular disease

BACKGROUND: Hypertension and cognitive impairment are prevalent in older people. It is known that hypertension is a direct risk factor for vascular dementia and recent studies have suggested hypertension also impacts upon prevalence of Alzheimer's disease. The question is therefore whether treatment of hypertension lowers the rate of cognitive decline. OBJECTIVES: To assess the effects of blood pressure lowering treatments for the prevention of dementia and cognitive decline in patients with hypertension but no history of cerebrovascular disease. SEARCH STRATEGY: The trials were identified through a search of CDCIG's Specialised Register, CENTRAL, MEDLINE, EMBASE, PsycINFO and CINAHL on 27 April 2005. SELECTION CRITERIA: Randomized, double-blind, placebo controlled trials in which pharmacological or non-pharmacological interventions to lower blood pressure were given for at least six months. DATA COLLECTION AND ANALYSIS: Two independent reviewers assessed trial quality and extracted data. The following outcomes were assessed: incidence of dementia, cognitive change from baseline, blood pressure level, incidence and severity of side effects and quality of life. MAIN RESULTS: Three trials including 12,091 hypertensive subjects were identified. Average age was 72.8 years. Participants were recruited from industrialised countries. Mean blood pressure at entry across the studies was 170/84 mmHg. All trials instituted a stepped care approach to hypertension treatment, starting with a calcium-channel blocker, a diuretic or an angiotensin receptor blocker. The combined result of the three trials reporting incidence of dementia indicated no significant difference between treatment and placebo (Odds Ratio (OR) = 0.89, 95% CI 0.69, 1.16). Blood pressure reduction resulted in a 11% relative risk reduction of dementia in patients with no prior cerebrovascular disease but this effect was not statistically significant (p = 0.38) and there was considerable heterogeneity between the trials. The combined results from the two trials reporting change in Mini Mental State Examination (MMSE) did not indicate a benefit from treatment (Weighted Mean Difference (WMD) = 0.10, 95% CI -0.03, 0.23). Both systolic and diastolic blood pressure levels were reduced significantly in the two trials assessing this outcome (WMD = -7.53, 95% CI -8.28, -6.77 for systolic blood pressure, WMD = -3.87, 95% CI -4.25, -3.50 for diastolic blood pressure).Two trials reported adverse effects requiring discontinuation of treatment and the combined results indicated a significant benefit from placebo (OR = 1.18, 95% CI 1.06, 1.30). When analysed separately, however, more patients on placebo in SCOPE were likely to discontinue treatment due to side effects; the converse was true in SHEP 1991. Quality of life data could not be analysed in the three studies. There was difficulty with the control group in this review as many of the control subjects received antihypertensive treatment because their blood pressures exceeded pre-set values. In most cases the study became a comparison between the study drug against a usual antihypertensive regimen. AUTHORS' CONCLUSIONS: There was no convincing evidence from the trials identified that blood pressure lowering prevents the development of dementia or cognitive impairment in hypertensive patients with no apparent prior cerebrovascular disease. There were significant problems identified with analysing the data, however, due to the number of patients lost to follow-up and the number of placebo patients given active treatment. This introduced bias. More robust results may be obtained by analysing one year data to reduce differential drop-out or by conducting a meta-analysis using individual patient data.

An Investigation of the Flow Field through a Variable Geometry Turbine Stator with Vane Endwall Clearance

Variable geometry turbines provide an extra degree of flexibility in air management in turbocharged engines. The pivoting stator vanes used to achieve the variable turbine geometry necessitate the inclusion of stator vane endwall clearances. The consequent leakage flow through the endwall clearances impacts the flow in the stator vane passages and an understanding of the impact of the leakage flow on stator loss is required. A numerical model of a typical variable geometry turbine was developed using the commercial CFX-10 computational fluid dynamics software, and validated using laser doppler velocimetry and static pressure measurements from a variable geometry turbine with stator vane endwall clearance. Two different stator vane positions were investigated, each at three different operating conditions representing different vane loadings. The vane endwall leakage was found to have a significant impact on the stator loss and on the uniformity of flow entering the turbine rotor. The leakage flow changed considerably at different vane positions and flow incidence at vane inlet was found to have a significant impact.

Speech Recognition with unknown partial feature corruption - a review of the union model

This paper provides a summary of our studies on robust speech recognition based on a new statistical approach – the probabilistic union model. We consider speech recognition given that part of the acoustic features may be corrupted by noise. The union model is a method for basing the recognition on the clean part of the features, thereby reducing the effect of the noise on recognition. To this end, the union model is similar to the missing feature method. However, the two methods achieve this end through different routes. The missing feature method usually requires the identity of the noisy data for noise removal, while the union model combines the local features based on the union of random events, to reduce the dependence of the model on information about the noise. We previously investigated the applications of the union model to speech recognition involving unknown partial corruption in frequency band, in time duration, and in feature streams. Additionally, a combination of the union model with conventional noise-reduction techniques was studied, as a means of dealing with a mixture of known or trainable noise and unknown unexpected noise. In this paper, a unified review, in the context of dealing with unknown partial feature corruption, is provided into each of these applications, giving the appropriate theory and implementation algorithms, along with an experimental evaluation.

Analytical calculation of far infrared spectra of ice in terms of a molecular model

Wideband far infrared (FIR) spectra of complex permittivity e(p) of ice are calculated in terms of a simple analytical theory based on the method of dipolar autocorrelation functions. The molecular model represents a revision of the model recently presented for liquid water in Adv. Chem. Phys. 127 (2003) 65. A composite two-fractional model is proposed. The model is characterised by three phenomenological potential wells corresponding to the three FIR bands observed in ice. The first fraction comprises dipoles reorienting in a rather narrow and deep hat-like well; these dipoles generate the librational band centred at the frequency approximate to 880 cm(-1). The second fraction comprises elastically interacting particles; they generate two nearby bands placed around frequency 200 cm(-1). For description of one of these bands the harmonic oscillator (HO) model is used, in which translational oscillations of two charged molecules along the H-bond are considered. The other band is produced by the H-bond stretch, which governs hindered rotation of a rigid dipole. Such a motion and its dielectric response are described in terms of a new cut parabolic (CP) model applicable for any vibration amplitude. The composite hat-HO-CP model results in a smooth epsilon(nu) ice spectrum, which does not resemble the noise-like spectra of ice met in the known literature. The proposed theory satisfactorily agrees with the experimental ice spectrum measured at - 7 degrees C. The calculated longitudinal optic-transverse optic (LO-TO) splitting occurring at approximate to 250 cm(-1) qualitatively agrees with the measured data. (c) 2004 Elsevier B.V. All rights reserved.

Towards agent-oriented model-driven architecture

Model Driven Architecture supports the transformation from reusable models to executable software. Business representations, however, cannot be fully and explicitly represented in such models for direct transformation into running systems. Thus, once business needs change, the language abstractions used by MDA (e.g. Object Constraint Language / Action Semantics), being low level, have to be edited directly. We therefore describe an Agent-oriented Model Driven Architecture (AMDA) that uses a set of business models under continuous maintenance by business people, reflecting the current business needs and being associated with adaptive agents that interpret the captured knowledge to behave dynamically. Three contributions of the AMDA approach are identified: 1) to Agent-oriented Software Engineering, a method of building adaptive Multi-Agent Systems; 2) to MDA, a means of abstracting high level business-oriented models to align executable systems with their requirements at runtime; 3) to distributed systems, the interoperability of disparate components and services via the agent abstraction.