'A Romanian Perspective on Brian Friel's Translations'

Based on the premise that the history of the representation in drama of the Ulster "Troubles" has been characterised by a move from direct to metaphorical engagement, this paper seeks to explore the signficance of Brian Friel's Translations as a "Troubles Drama" with reference to a production of the play I directed for the Hungarian Theater of Cluj in the Fall of 2001. Interpreting a play about language in a language other than the one in which it was originally written proved to have many implications for the rehearsal process and led me to experiment with the image theatre techniques of Augusto Boal. The nature of Cluj/Kolozsvar as a bi-lingual city added to the complexities of the process, as did my own status as an English-speaking director in a Hungarian-speaking environment. The extraordinary neautre of the wider geopolitical context at the time of the production proved to be the final ingredient in what became an exceptional empirical process of discovery. The discussion of the particular production is placed in the wider context of an exposition of a theory of "cultural gravity" as an alternative to "liminality" in helping to assess the cultural signficance of geopolitical boundaries.

Multi-Modal CTL:Completeness, Complexity, and an Application

We define a multi-modal version of Computation Tree Logic (ctl) by extending the language with path quantifiers E and A where d denotes one of finitely many dimensions, interpreted over Kripke structures with one total relation for each dimension. As expected, the logic is axiomatised by taking a copy of a ctl axiomatisation for each dimension. Completeness is proved by employing the completeness result for ctl to obtain a model along each dimension in turn. We also show that the logic is decidable and that its satisfiability problem is no harder than the corresponding problem for ctl. We then demonstrate how Normative Systems can be conceived as a natural interpretation of such a multi-dimensional ctl logic. © 2009 Springer Science+Business Media B.V.

Integrating textual analysis and evidential reasoning for decision making in Engineering design

Decision making is an important element throughout the life-cycle of large-scale projects. Decisions are critical as they have a direct impact upon the success/outcome of a project and are affected by many factors including the certainty and precision of information. In this paper we present an evidential reasoning framework which applies Dempster-Shafer Theory and its variant Dezert-Smarandache Theory to aid decision makers in making decisions where the knowledge available may be imprecise, conflicting and uncertain. This conceptual framework is novel as natural language based information extraction techniques are utilized in the extraction and estimation of beliefs from diverse textual information sources, rather than assuming these estimations as already given. Furthermore we describe an algorithm to define a set of maximal consistent subsets before fusion occurs in the reasoning framework. This is important as inconsistencies between subsets may produce results which are incorrect/adverse in the decision making process. The proposed framework can be applied to problems involving material selection and a Use Case based in the Engineering domain is presented to illustrate the approach. © 2013 Elsevier B.V. All rights reserved.

England, Neo-Latin, and the Continental Journey: Linguistic and Textual Itineraries

This chapter examines the ramifications of continental travel and associated epistolary communication for English poets of the period. It argues that recourse to neo-Latin, the universal language of diplomacy, served not only to establish a sense of shared space—linguistic, cultural, generic—between England and the continent, but also to signal self-conscious differences (climatic, geographical, historical, political) between England and her continental peers. Through an investigation of a range of ‘performances’ on stages that were ‘academic’, poetic, autobiographical, and epistolographic, it assesses the central role of neo-Latin as a language that underwent a series of textual itineraries. These ‘itineraries’ manifest themselves in a number of ways. Neo-Latin as a shared linguistic medium can facilitate, and quite uniquely so, intertextual engagement with the classics, but now ancient Rome, its language, its mythology, its hierarchy of genres, are viewed through a seventeenth-century lens and appropriated by poets in both England and Italy to describe contemporary events, whether personal, or political. Close examination of the neo-Latin poetry of Milton and Marvell reveals, it is argued, a self-fashioning coloured by such textual itineraries and interchanges. The absorption and replication of continental literary and linguistic methodologies (the academic debate; the etymological play of Marinism; the hybridity of neo-Latin and Italian voices) reveal in short a linguistic and textual reciprocity that gave birth to something very new.

Knowledge Management Techniques to Augment Textual CBR (PhD Thesis)

The past decade had witnessed an unprecedented growth in the amount of available digital content, and its volume is expected to continue to grow the next few years. Unstructured text data generated from web and enterprise sources form a large fraction of such content. Many of these contain large volumes of reusable data such as solutions to frequently occurring problems, and general know-how that may be reused in appropriate contexts. In this work, we address issues around leveraging unstructured text data from sources as diverse as the web and the enterprise within the Case-based Reasoning framework. Case-based Reasoning (CBR) provides a framework and methodology for systematic reuse of historical knowledge that is available in the form of problemsolution
pairs, in solving new problems. Here, we consider possibilities of enhancing Textual CBR systems under three main themes: procurement, maintenance and retrieval. We adapt and build upon the stateof-the-art techniques from data mining and natural language processing in addressing various challenges therein. Under procurement, we investigate the problem of extracting cases (i.e., problem-solution pairs) from data sources such as incident/experience
reports. We develop case-base maintenance methods specifically tuned to text targeted towards retaining solutions such that the utility of the filtered case base in solving new problems is maximized. Further, we address the problem of query suggestions for textual case-bases and show that exploiting the problem-solution partition can enhance retrieval effectiveness by prioritizing more useful query suggestions. Additionally, we illustrate interpretable clustering as a tool to drill-down to domain specific text collections (since CBR systems are usually very domain specific) and develop techniques for improved similarity assessment in social media sources such as microblogs. Through extensive empirical evaluations, we illustrate the improvements that we are able to
achieve over the state-of-the-art methods for the respective tasks.

Language Experience Affects Grouping of Musical Instrument Sounds

Language experience clearly affects the perception of speech, but little is known about whether these differences in perception extend to non-speech sounds. In this study, we investigated rhythmic perception of non-linguistic sounds in speakers of French and German using a grouping task, in which complexity (variability in sounds, presence of pauses) was manipulated. In this task, participants grouped sequences of auditory chimeras formed from musical instruments. These chimeras mimic the complexity of speech without being speech. We found that, while showing the same overall grouping preferences, the German speakers showed stronger biases than the French speakers in grouping complex sequences. Sound variability reduced all participants' biases, resulting in the French group showing no grouping preference for the most variable sequences, though this reduction was attenuated by musical experience. In sum, this study demonstrates that linguistic experience, musical experience, and complexity affect rhythmic grouping of non-linguistic sounds and suggests that experience with acoustic cues in a meaningful context (language or music) is necessary for developing a robust grouping preference that survives acoustic variability.