Space–Time Signal Analysis and the 3D Shearlet Transform

In this work, we address the problem of analyzing video sequences by representing meaningful local space–time neighborhoods. We propose a mathematical model to describe relevant points as local singularities of a 3D signal, and we show that these local patterns can be nicely highlighted by the 3D shearlet transform, which is at the root of our work. Based on this mathematical framework, we derive an algorithm to represent space–time points which is very effective in analyzing video sequences. In particular, we show how points of the same nature have a very similar representation, allowing us to compute different space–time primitives for a video sequence in an unsupervised way.     

Joining the blunt and the pointy end of the spear: towards a common framework of joint action,human–machine cooperation,cooperative guidance and control,shared, traded and supervisory control

To introduce this special issue of shared and cooperative control, we will look into history of tools in cooperation between humans and aim to unify the plethora of related concepts and definitions that have been proposed in recent years, such as shared control, human–machine cooperation and cooperative guidance and control. Concretely, we provide definitions to relate these concepts and sketch a unifying framework of shared and cooperative control that sees the different concepts as different perspectives or foci on a common design space of shared intentionality, control and cooperation between humans and machines. One working hypothesis which the article explores is that shared control can be understood as cooperation at the control layer, while human–machine cooperation can include shared control, but can also extend towards cooperation at higher layers, e.g., of guidance and navigation, of maneuvers and goals. The relationship between shared control and human–machine cooperation is compared to the relationship between the sharp, pointy tip and the (blunt) shaft of a spear. Shared control is where cooperation comes sharply into effect at the control layer, but to be truly effective it should be supported by cooperation on all layers beyond the operational layer, e.g., on the tactical and strategic layer. A fourth layer addresses the meta-communication about the cooperation and supports the other three layers in a traversal way.

     

The Eigenvalue Problem for the 2D Laplacian in ℋ-Matrix Arithmetic and Application to the Heat and Wave Equation

A class of matrices (-matrices) has recently been introduced by Hackbusch for approximating large and fully populated matrices arising from FEM and BEM applications. These matrices are data-sparse and allow approximate matrix operations of almost linear complexity. In the present paper, we choose a special class of -matrices that provides a good approximation to the inverse of the discrete 2D Laplacian. For these 2D -matrices we study the blockwise recursive schemes for block triangular linear systems of equations and the Cholesky and LDL^T factorization in an approximate arithmetic of almost linear complexity. Using the LDL^T factorization we compute eigenpairs of the discrete 2D Laplacian in -matrix arithmetic by means of a so-called simultaneous iteration for computing invariant subspaces of non-Hermitian matrices due to Stewart. We apply the -matrix techniques to approximate the solutions of the high-frequency 2D wave equation for smooth initial data and the 2D heat equation for arbitrary initial data by spectral decomposition of the discrete 2D Laplacian in, up to logarithmic factors, optimal complexity.     

On the computation of the 〈3, 4, 5〉 curve skeleton of 3D objects

An algorithm to compute the curve skeleton of 3D objects in voxel images is presented. The skeleton is stable under isometric transformations of the object, since the algorithm is based on the use of the 〈3, 4, 5〉 weighted distance transform, which is a good approximation of the Euclidean distance transform. The 〈3, 4, 5〉 weighted distance transform is used both to identify suitable anchor points, and to efficiently check object voxels according to their distance to the background. The curve skeleton is symmetrically placed within the object, is topologically equivalent to the object, is unit-wide and provides a satisfactory representation of the object. Though the size of the object reconstructed from the curve skeleton via the reverse distance transformation is not as thick as that of the input, shape information is mostly retained by the skeleton, since all regions perceived as significant in the input can still be found in the reconstructed object.     

Managing the Digitization and Online Publication of Sensitive Heritage Material in the Dúchas Project

The Dúchas project involves the digitization of heritage material collected in the Irish Folklore Commission Schools’ Scheme. This collection contains a small amount of stories that make derogatory reference to named individuals or families. Digitization and publication in an online database makes the sharing of this material online remarkably easy. To this end, a set of guidelines regarding the identification of sensitive material has been developed and pages marked as containing such material are automatically withheld. This article discusses the formulation of those guidelines as well as the technical solution for withholding such material.     

“Missing women”: Gender,ICTs, and the shaping of the global economy

In a key article (Walsham & Sahay, 2005) outlining research on information systems in developing countries and suggesting potential areas for future research, a notable omission was the issue of gender and gender relations. In this article, we draw on the substantial gender and development literature to demonstrate the centrality of gender to our understanding of information systems (IS) in developing countries. In particular, we consider the relationship among gender, information and communication technologies (ICTs), and globalization to illustrate how changes in the global economy both impact on and are influenced by changing gender identities and roles. © 2008 Wiley Periodicals, Inc.     

On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality

The classification problem is considered in which an outputvariable y assumes discrete values with respectiveprobabilities that depend upon the simultaneous values of a set of input variablesx = {x_1,....,x_n}. At issue is how error in the estimates of theseprobabilities affects classification error when the estimates are used ina classification rule. These effects are seen to be somewhat counterintuitive in both their strength and nature. In particular the bias andvariance components of the estimation error combine to influenceclassification in a very different way than with squared error on theprobabilities themselves. Certain types of (very high) bias can becanceled by low variance to produce accurate classification. This candramatically mitigate the effect of the bias associated with some simpleestimators like naive Bayes, and the bias induced by thecurse-of-dimensionality on nearest-neighbor procedures. This helps explainwhy such simple methods are often competitive with and sometimes superiorto more sophisticated ones for classification, and whybagging/aggregating classifiers can often improveaccuracy. These results also suggest simple modifications to theseprocedures that can (sometimes dramatically) further improve theirclassification performance.     

Reconstructing the Equation of State in Holographic Dark Energy in 5D Brans-Dicke Theory,and Comparison with ΛCDM Model and CPL Parametrization

We study Holographic dark energy in 5D Brans-Dicke cosmology. To investigate the stability and attractor solutions, we fit the model with the SNIa and Gamma-Ray Burst (GRB) observational data. We also examine the holographic nature of dark energy in the model through the equation of state (EoS). In addition, a reconstructed form of the EoS from holographic dark energy on the model is driven The model strongly exhibits the present cosmic accelerating. It also shows that the universe starts from an unstable radiation-dominated epoch and reaches a stable late-time accelerated phase originating from holographic dark energy in the Brans-Dicke model.     

“Extra-Ordinary” Ergonomics: How to Accommodate Small and Big Persons,the Disabled and Elderly,Expectant Mothers,and Children

Abstract

Data from a previous study of soldier driving postures and seating positions were analysed to develop statistical models for defining accommodation of driver seating positions in military vehicles. Regression models were created for seating accommodation applicable to driver positions with a fixed heel point and a range of steering wheel locations in typical tactical vehicles. The models predict the driver-selected seat position as a function of population anthropometry and vehicle layout. These models are the first driver accommodation models considering the effects of body armor and body-borne gear. The obtained results can benefit the design of military vehicles, and the methods can also be extended to be utilised in the development of seating accommodation models for other driving environments where protective equipment affects driver seating posture, such as vehicles used by law-enforcement officers and firefighters.

Practitioner Summary: A large-scale laboratory study of soldier driving posture and seating position was designed to focus on tactical vehicle (truck) designs. Regression techniques are utilised to develop accommodation models suitable for tactical vehicles. These are the first seating accommodation models based on soldier data to consider the effects of personal protective equipment and body-borne gear.     

Estimating actual distances by norm functions: a comparison between the lk,p,θ-norm and the lb1,b2,θ-norm and a study about the selection of the data set

The aim of this paper is two-fold. First, the weighted l_p-norm, which has proved to be an accurate distance predicting function and has been proposed by several authors as the most suitable predictor of distances, is compared through an empirical study with the l_2b-norm, a function with the same number of parameters as the first one. The results show that neither distance function dominates the other. On the contrary, depending on the region considered either norm may be significantly better than the other. The second aim is to investigate how the selection of the data set representing the network of the region affects the ability of the distance predicting function for predicting distances, and to try to deduce how to obtain a suitable data set which adequately represents a given geographical region. Through another empirical study it is shown that the selection of the data set dramatically affects the accuracy of the predictions. To obtain a suitable data set it is important to choose a good sample size, and more importantly, the cities should be chosen so that they are distributed all over the region and represent the density of the cities in the region.