‘Souvenirs, souvenirs': the role of memory in the work of Annie Saumont

The work of nouvelliste Annie Saumont constantly explores the phenomenon of memory, and of memories. This article identifies and nuances the various forms that this exploration takes. An introductory contextualization of author and theme is followed by the presentation of a short story, ‘Méandres’, which embodies the first quality of memory to be examined: its capacity not only to recall but also to re-evaluate a past which is thus shown to be as hypothetical as the future. Memory as guilt that moulds or puts its indelible stamp on lives is then evoked by means of examples from other stories, illustrating the gradations Saumont achieves in her investigation of the power of this complex faculty. The next section turns to her portrayal of involuntary memory. Unlike for Proust, the instances of spontaneous remembering that are experienced by her characters lunge at them down the years almost exclusively to wound or disorientate. Depictions of the memory which conserves, and is thus burdened by, secrets are then considered, and finally Saumont's evocation of characters who have different reasons to analyse the way their own and other people's memories work. The conclusion to be drawn is that for Saumont, we are our memories; the ability to master a ‘judicious interpretation’ of memory – or indeed, to forget – is, in her stories, overwhelmingly a quality to be envied.

Development of a semantic graph-based scene description

Software representations of scenes, i.e. the modelling of objects in space, are used in many application domains. Current modelling and scene description standards focus on visualisation dimensions, and are intrinsically limited by their dependence upon their semantic interpretation and contextual application by humans. In this paper we propose the need for an open, extensible and semantically rich modelling language, which facilitates a machine-readable semantic structure. We critically review existing standards and techniques, and highlight a need for a semantically focussed scene description language. Based on this defined need we propose a preliminary solution, based on hypergraph theory, and reflect on application domains.

Memory effects in liquid crystal elastomers

Free-standing monodomain liquid crystal elastomer samples are shown to have a complete memory of the orientational configuration at the time of cross-linking. This memory is demonstrated through samples in which the parent polymer system is first aligned in a magnetic field prior to cross-linking. These films show reversible nematic-isotropic phase transitions and x-ray scattering patterns characteristic of nematic phases. The liquid crystal elastomer films exhibit a remarkable memory effect, in that the sample may be held at temperatures well above the nematic-isotropic transition for extended periods ( > 2 weeks), but on cooling into the liquid crystal phase region, both the original director alignment and the degree of preferred orientation are recovered. It is demonstrated that these novel memory effects are equilibrium in nature. The origins of this phenomena in terms of coupling between the mesogenic side-chains and the polymer network are discussed.

Coupling and memory in liquid crystal elastomers

The polymer backbone of a side-chain liquid crystal polymer exhibits an anisotropic shape due to the coupling of the liquid crystal orientational order of the mesogenic side-chains to the backbone. The magnitude and sign of this coupling may be controlled by chemical design. The introduction of chemical cross-links in to such a system provides both a memory of the anisotropic organisation and a mechanism by which the microscopic anisotropy can be realised at a macroscopic level. We show how this anisotropic network structure yields new phenomena when electric or mechanical fields are applied.

Social networks: evolving graphs with memory dependent edges

The plethora, and mass take up, of digital communication tech- nologies has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the ex- istence or otherwise of certain infinite products and series involving age dependent model parameters. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

HR-semantics roadmap: the semantic challenges and opportunities in the Human Resources domain

Purpose: This document identifies the challenges and opportunities in applying the ontology technology in the Human Resources domain. Target users: A reference for both the HR and the ontology communities. Also, to be used as a roadmap for the OOA itself, within the HR domain. Background: During the discussion panel at the OOA kick-off workshop, which was attended by more than 50 HR and ontology experts, the need for this roadmap was realized. It was obvious that the current understanding of the problem of semantics in HR is fragmented and only partial solutions exist. People from both the HR and the ontology communities speak different languages, have different understandings, and are not aware of existing solutions.

Disentangling multi-level systems: averaging, correlations and memory

We consider two weakly coupled systems and adopt a perturbative approach based on the Ruelle response theory to study their interaction. We propose a systematic way of parameterizing the effect of the coupling as a function of only the variables of a system of interest. Our focus is on describing the impacts of the coupling on the long term statistics rather than on the finite-time behavior. By direct calculation, we find that, at first order, the coupling can be surrogated by adding a deterministic perturbation to the autonomous dynamics of the system of interest. At second order, there are additionally two separate and very different contributions. One is a term taking into account the second-order contributions of the fluctuations in the coupling, which can be parameterized as a stochastic forcing with given spectral properties. The other one is a memory term, coupling the system of interest to its previous history, through the correlations of the second system. If these correlations are known, this effect can be implemented as a perturbation with memory on the single system. In order to treat this case, we present an extension to Ruelle's response theory able to deal with integral operators. We discuss our results in the context of other methods previously proposed for disentangling the dynamics of two coupled systems. We emphasize that our results do not rely on assuming a time scale separation, and, if such a separation exists, can be used equally well to study the statistics of the slow variables and that of the fast variables. By recursively applying the technique proposed here, we can treat the general case of multi-level systems.