University of Portsmouth

About: University of Portsmouth is a education organization based out in Portsmouth, Portsmouth, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 5452 authors who have published 14256 publications receiving 424346 citations. The organization is also known as: Portsmouth and Gosport School of Science and Art & Portsmouth and Gosport School of Science and the Arts.

Physical capital and situated action:a new direction for corporeal sociology

Abstract: Pierre Bourdieu's writings provide us with a powerful vision of corporeal sociology (an approach towards human relationships and identities that has at its centre the socially shaped embodied subject), and an understanding of the body as a form of physical capital. Despite his protestations to the contrary, however, a reproductionist bias pervades Bourdieu's conception of social action, making it difficult for him to account theoretically for those individuals who deviate from the class trajectories ‘assigned’ them during their formative years. After exploring the idea of physical capital implicit within Bourdieu's work, this article places this conception of the body on a non‐reproductionist footing by developing the pragmatist notion of situated action. This conception of action is then used to illustrate how the relationship between social field and physical capital can result in not only a continuation of habitual action (and an associated accumulation of particular quantities and qualities of physica...

Large-scale bias and efficient generation of initial conditions for nonlocal primordial non-Gaussianity

Abstract: We study the scale dependence of halo bias in generic (nonlocal) primordial non-Gaussian (PNG) initial conditions of the type motivated by inflation, parametrized by an arbitrary quadratic kernel. We first show how to generate nonlocal PNG initial conditions with minimal overhead compared to local PNG models for a general class of primordial bispectra that can be written as linear combinations of separable templates. We run cosmological simulations for the local, and nonlocal equilateral and orthogonal models and present results on the scale dependence of halo bias. We also derive a general formula for the Fourier-space bias using the peak-background split in the context of the excursion-set approach to halos and discuss the difference and similarities with the known corresponding result from local bias models. Our peak-background split bias formula generalizes previous results in the literature to include non-Markovian effects and nonuniversality of the mass function and are in better agreement with measurements in numerical simulations than previous results for a variety of halo masses, redshifts and halo definitions. We also derive for the first time quadratic bias results for arbitrary nonlocal PNG, and show that nonlinear bias loops give small corrections at large scales. The resulting well-behaved perturbation theory paves the way to constrain nonlocal PNG from measurements of the power spectrum and bispectrum in galaxy redshift surveys.

Decision Rule Approach

Abstract: In this chapter we present the methodology of Multiple-Criteria Decision Aiding (MCDA) based on preference modelling in terms of “if…, then …” decision rules. The basic assumption of the decision rule approach is that the decision maker (DM) accepts to give preference information in terms of examples of decisions and looks for simple rules justifying her decisions. An important advantage of this approach is the possibility of handling inconsistencies in the preference information, resulting from hesitations of the DM. The proposed methodology is based on the elementary, natural and rational principle of dominance. It says that if action x is at least as good as action y on each criterion from a considered family, then x is also comprehensively at least as good as y. The set of decision rules constituting the preference model is induced from the preference information using a knowledge discovery technique properly adapted in order to handle the dominance principle. The mathematical basis of the decision rule approach to MCDA is the Dominance-based Rough Set Approach (DRSA) developed by the authors. We present some basic applications of this approach, starting from multiple-criteria classification problems, and then going through decision under uncertainty, hierarchical decision making, classification problems with partially missing information, problems with imprecise information modelled by fuzzy sets, until multiple-criteria choice and ranking problems, and some classical problems of operations research. All these applications are illustrated by didactic examples whose aim is to show in an easy way how DRSA can be used in various contexts of MCDA.

Detecting deception via strategic disclosure of evidence.

Abstract: Deception detection research has largely neglected an important aspect of many investigations, namely that there often exists evidence against a suspect. This study examined the potentials of timing of evidence disclosure as a deception detection tool. The main prediction was that observers (N = 116) would obtain higher accuracy rates if the evidence against the suspects (N = 58) was presented in a late rather than early stage of the interrogation. This prediction was based on the idea that late evidence disclosure would trigger lack of consistencies between the liars’ stories and the evidence; this could be used as a cue to deception. The main prediction received support. Late disclosure observers obtained an overall accuracy of 61.7%, compared to 42.9% of Early disclosure observers. Deceptive statements were identified with high accuracy (67.6%) in Late disclosure, indicating that the technique in this form is beneficial mainly for pinpointing lies.

Rep on the block: A next generation reputation system based on the blockchain

Abstract: This paper presents the first generalized reputation system that can be applied to multiple networks that is based on the blockchain. We first discuss current reputation systems, conducting a critical analysis of their current security vulnerabilities, before looking at how new blockchain based technologies are used. We propose an innovative new reputation system that is based on blockchain technologies which aims to solve many unanswered questions in today's current generation reputation systems. We then consider the limitations of such a system, before using simulations and analyses to demonstrate methods of overcoming these limitations. We conclude by suggesting areas for future studies, and summarizing our findings.