Multi-Dimensional Deprivation in Ireland Among 9-Year-Olds in Ireland:An Analysis of the Growing Up in Ireland Survey’

In this paper we make use of the 9-year old wave of the Growing Up in Ireland study to analyse multidimensional deprivation in Ireland. The Alkire and Foster adjusted head count ratio approach (AHCR; 2007, 2011a, 2011b) applied here constitutes a significant improvement on union and intersection approaches and allows for the decomposition of multidimensional poverty in terms of dimensions and sub-groups. The approach involves a censoring of data such that deprivations count only for those above the specified multidimensional threshold leading to a stronger set of interrelationships between deprivation dimensions. Our analysis shows that the composition of the adjusted head ratio is influenced by a range of socio-economic factors. For less-favoured socio-economic groups dimensions relating to material deprivation are disproportionately represented while for the more advantaged groups, those relating to behavioral and emotional issues and social interaction play a greater role. Notwithstanding such variation in composition, our analysis showed that the AHCR varied systematically across categories of household type, and the social class, education and age group of the primary care giver. Furthermore, these variables combined in a cumulative manner. The most systematic variation was in relation to the head count of those above the multidimensional threshold rather than intensity, conditional on being above that cut-off point. Without seeking to arbitrate on the relative value of composite indices versus disaggregated profiles, our analysis demonstrates that there is much to be gained from adopting an approach with clearly understood axiomatic properties. Doing so allows one to evaluate the consequences of the measurement strategy employed for the understanding of levels of multidimensional deprivation, the nature of such deprivation profiles and socio-economic risk patterns. Ultimately it permits an informed assessment of the strengths and weaknesses of the particular choices made.

Scalable black-box prediction models for multi-dimensional adaptation on NUMA multi-cores

This paper presents a scalable, statistical ‘black-box’ model for predicting the performance of parallel programs on multi-core non-uniform memory access (NUMA) systems. We derive a model with low overhead, by reducing data collection and model training time. The model can accurately predict the behaviour of parallel applications in response to changes in their concurrency, thread layout on NUMA nodes, and core voltage and frequency. We present a framework that applies the model to achieve significant energy and energy-delay-square (ED2) savings (9% and 25%, respectively) along with performance improvement (10% mean) on an actual 16-core NUMA system running realistic application workloads. Our prediction model proves substantially more accurate than previous efforts.

Multi-Dimensional Simulations of the Expanding Supernova Remnant of SN 1987A

The expanding remnant from SN 1987A is an excellent laboratory for investigating the physics of supernovae explosions. There is still a large number of outstanding questions, such as the reason for the asymmetric radio morphology, the structure of the pre-supernova environment, and the efficiency of particle acceleration at the supernova shock. We explore these questions using three-dimensional simulations of the expanding remnant between days 820 and 10,000 after the supernova. We combine a hydrodynamical simulation with semi-analytic treatments of diffusive shock acceleration and magnetic field amplification to derive radio emission as part of an inverse problem. Simulations show that an asymmetric explosion, combined with magnetic field amplification at the expanding shock, is able to replicate the persistent one-sided radio morphology of the remnant. We use an asymmetric Truelove & McKee progenitor with an envelope mass of 10 M-circle dot and an energy of 1.5 x 10(44) J. A termination shock in the progenitor's stellar wind at a distance of 0 ''.43-0 ''.51 provides a good fit to the turn on of radio emission around day 1200. For the H II region, a minimum distance of 0 ''.63 +/- 0 ''.01 and maximum particle number density of (7.11 +/- 1.78) x 10(7) m(-3) produces a good fit to the evolving average radius and velocity of the expanding shocks from day 2000 to day 7000 after explosion. The model predicts a noticeable reduction, and possibly a temporary reversal, in the asymmetric radio morphology of the remnant after day 7000, when the forward shock left the eastern lobe of the equatorial ring.

Fast Rule Mining over Multi-dimensional Windows

Association rule mining is an indispensable tool for discovering
insights from large databases and data warehouses.
The data in a warehouse being multi-dimensional, it is often
useful to mine rules over subsets of data defined by selections
over the dimensions. Such interactive rule mining
over multi-dimensional query windows is difficult since rule
mining is computationally expensive. Current methods using
pre-computation of frequent itemsets require counting
of some itemsets by revisiting the transaction database at
query time, which is very expensive. We develop a method
(RMW) that identifies the minimal set of itemsets to compute
and store for each cell, so that rule mining over any
query window may be performed without going back to the
transaction database. We give formal proofs that the set of
itemsets chosen by RMW is sufficient to answer any query
and also prove that it is the optimal set to be computed
for 1 dimensional queries. We demonstrate through an extensive
empirical evaluation that RMW achieves extremely
fast query response time compared to existing methods, with
only moderate overhead in pre-computation and storage

An efficient numerical scheme for solving multi-dimensional fractional optimal control problems with a quadratic performance index

The shifted Legendre orthogonal polynomials are used for the numerical solution of a new formulation for the multi-dimensional fractional optimal control problem (M-DFOCP) with a quadratic performance index. The fractional derivatives are described in the Caputo sense. The Lagrange multiplier method for the constrained extremum and the operational matrix of fractional integrals are used together with the help of the properties of the shifted Legendre orthonormal polynomials. The method reduces the M-DFOCP to a simpler problem that consists of solving a system of algebraic equations. For confirming the efficiency and accuracy of the proposed scheme, some test problems are implemented with their approximate solutions.

New conserved vorticity integrals for moving surfaces in multi-dimensional fluid flow

For inviscid fluid flow in any n-dimensional Riemannian manifold, new conserved vorticity integrals generalizing helicity, enstrophy, and entropy circulation are derived for lower-dimensional surfaces that move along fluid streamlines. Conditions are determined for which the integrals yield constants of motion for the fluid. In the case when an inviscid fluid is isentropic, these new constants of motion generalize Kelvin’s circulation theorem from closed loops to closed surfaces of any dimension.

A data forest: multi-dimensional visualization

As Terabyte datasets become the norm, the focus has shifted away from our ability to produce and store ever larger amounts of data, onto its utilization. It is becoming increasingly difficult to gain meaningful insights into the data produced. Also many forms of the data we are currently producing cannot easily fit into traditional visualization methods. This paper presents a new and novel visualization technique based on the concept of a Data Forest. Our Data Forest has been designed to be used with vir tual reality (VR) as its presentation method. VR is a natural medium for investigating large datasets. Our approach can easily be adapted to be used in a variety of different ways, from a stand alone single user environment to large multi-user collaborative environments. A test application is presented using multi-dimensional data to demonstrate the concepts involved.

Assessing sport management journals : a multi-dimensional examination

The rating of refereed journals has become important for academics and institutions as well as for sport management as a field of study. This paper argues that the dearth of a rating system in sport management works against the best interests of the development of the field. This paper presents a rating scheme for sport management journals, which replicates an earlier study of marketing journals, using weighted multi-dimensional perceptual ratings (Polonsky & Whitelaw, 2006). Forty-five senior sport management academics evaluated 13 journals on four criteria: journal prestige, contribution to theory, contribution to practice and contribution to teaching. Using the weighted scores of the four criteria for each journal and a supporting cluster analysis, four categories of journals were identified. The results of this study will assist academics as they argue the case for the quality of journals in which they publish. Further it facilitates evaluation of sport management journals in relation to one another on the basis of their overall ranking and their scores on the four individual criteria.