Hamiltonian mappings and circle packing phase spaces.

We introduce three area preserving maps with phase space structures which resemble circle packings. Each mapping is derived from a kicked Hamiltonian system with one of the three different phase space geometries (planar, hyperbolic or spherical) and exhibits an infinite number of coexisting stable periodic orbits which appear to ‘pack’ the phase space with circular resonances.

A physical packing sequence algorithm for the container loading problem with static mechanical equilibrium conditions

The container loading problem (CLP) is a combinatorial optimization problem for the spatial arrangement of cargo inside containers so as to maximize the usage of space. The algorithms for this problem are of limited practical applicability if real-world constraints are not considered, one of the most important of which is deemed to be stability. This paper addresses static stability, as opposed to dynamic stability, looking at the stability of the cargo during container loading. This paper proposes two algorithms. The first is a static stability algorithm based on static mechanical equilibrium conditions that can be used as a stability evaluation function embedded in CLP algorithms (e.g. constructive heuristics, metaheuristics). The second proposed algorithm is a physical packing sequence algorithm that, given a container loading arrangement, generates the actual sequence by which each box is placed inside the container, considering static stability and loading operation efficiency constraints.

Exploiting the bin-class histograms for feature selection on discrete data

In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.

Effects of grain shape on packing and dilatancy of sheared granular materials

Aus: Soft matter, Vol. 10.2014, H. 28, S. 5157 - 5167

Comparing population distributions from bin-aggregated sample data: an application to historical height data from France

This paper develops a methodology to estimate the entire population distributions from bin-aggregated sample data. We do this through the estimation of the parameters of mixtures of distributions that allow for maximal parametric flexibility. The statistical approach we develop enables comparisons of the full distributions of height data from potential army conscripts across France's 88 departments for most of the nineteenth century. These comparisons are made by testing for differences-of-means stochastic dominance. Corrections for possible measurement errors are also devised by taking advantage of the richness of the data sets. Our methodology is of interest to researchers working on historical as well as contemporary bin-aggregated or histogram-type data, something that is still widely done since much of the information that is publicly available is in that form, often due to restrictions due to political sensitivity and/or confidentiality concerns.

Are you packing a healthy lunch? (English and Irish)

This booklet is designed toimprove pupils' nutrition and implement healthier eating and drinking practices. It containspractical tips for parents, carers and children on how to pack an appetising, healthy lunchbox.

Packing a healthy punch for lunch

In Northern Ireland over 127,000 children bring their own food to school so it is important to ensure that food is both appetising and is good for health. Recent surveys looking at Childrens lunchboxes revealed that they are often too high in fat, salt and sugar, with just under half of the lunchboxes containing no fruit. To help parents and carers make lunchboxes healthier, the PHA has produced a leaflet, Are you packing a healthy lunch? in collaboration with safefood, the Department of Health, Social Services and Public Safety and the Department of Education.It will be distributed to every child in primary school and contains practical tips for parents, carers and children on how to pack an appetising, healthy lunchbox.

Are you packing a healthy lunch? (English and Irish)

This booklet is designed to�improve pupils' nutrition and implement healthier eating and drinking practices. It contains�practical tips for parents, carers and children on how to pack an appetising, healthy lunchbox.

MIinimal N-point diameters and f-best-packing constants in Rd[superindex]

Vegeu el resum a l'inici del document de l'arxiu adjunt

How do coil configuration and packing density influence intra-aneurysmal hemodynamics?

Endovascular coiling is a well-established therapy for treating intracranial aneurysms. Nonetheless, postoperative hemodynamic changes induced by this therapy remain not fully understood. The purpose of this work is to assess the influence of coil configuration and packing density on intra-aneurysmal hemodynamics