High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Adaptive Cognitive Interaction Systems

Adaptive kognitive Interaktionssysteme beobachten und modellieren den Zustand ihres Benutzers und passen das Systemverhalten entsprechend an. Ein solches System besteht aus drei Komponenten: Dem empirischen kognitiven Modell, dem komputationalen kognitiven Modell und dem adaptiven Interaktionsmanager. Die vorliegende Arbeit enthält zahlreiche Beiträge zur Entwicklung dieser Komponenten sowie zu deren Kombination. Die Ergebnisse werden in zahlreichen Benutzerstudien validiert

Machine Learning for Auditory Hierarchy

Coleman, W. (2021). Machine Learning for Auditory Hierarchy. This dissertation is submitted for the degree of Doctor of Philosophy, Technological University Dublin. Audio content is predominantly delivered in a stereo audio file of a static, pre-formed mix. The content creator makes volume, position and effects decisions, generally for presentation in stereo speakers, but has no control ultimately over how the content will be consumed. This leads to poor listener experience when, for example, a feature film is mixed such that the dialogue is at a low level relative to the sound effects. Consumers can complain that they must turn the volume up to hear the words, but back down again because the effects levels are too loud. Addressing this problem requires a television mix optimised for the stereo speakers used in the vast majority of homes, which is not always available

CIRCUS 2001 Conference Proceedings: New Synergies in Digital Creativity. Conference for Content Integrated Research in Creative User Systems

CIRCUS (Content Integrated Research For Creative User Systems) was an ESPRIT Working Group, originally set up in 1988 as one of the very last additional actions in Framework 4, under DG III. Its purpose was to develop models for collaborative work between artists (the term here used in its widest sense) and technologists (ditto) and to promote these models by whatever means available. While some have criticised this aim as implicitly promoting a 1950s agenda of building bridges across C.P. Snow’s ‘two cultures’, there is no such intention here, rather that technology, particularly computer and communications technology (ICT) , is irresistibly intruding into what is normally thought of as creative work (and so practised by artists) and that, like any new technique, this has to be understood by its potential practitioners in terms of its true strengths and limitations. The specific problem that computer technology poses is that it is in principle malleable to such an extent that the limitations on its form and functionality are still barely understood, yet the people charged with the task of making the technology available have little or no understanding of the needs of creative users. What the artist usually sees is a tool which is in principle capable of being harnessed to creative ends but in practice resists being so applied. Quite often the tool is shaped more by blind economic forces than by a clear response to a specific, here creative, need. CIRCUS came into existence as a forum in which both artists and technologists could work out how best to play to the strengths of ICT and how to apply both creative and technological solutions (possibly both together) to its limitations. In particular the then new Framework V programme invited projects in such areas as new media but required them to be addressed in essentially the same old way, by technologists working towards commercialisation. The only obvious exception to this was in the area of cultural heritage which, incidentally, CIRCUS was also capable of reviewing. The scope for effective participation by artists was thus limited by an essentially technological agenda although everybody at the time, the participants of CIRCUS and programme managers in DG III, believed that we could do far better than this, and to develop new models of working which could inform the nature of Framework VI or even the later stages of F V. It is fair to say that everyone involved was excited by the idea of doing something quite new (and iconoclastic), not least the expanding of the expertise base on which future Frameworks could draw. It is also fair to say that, while not ultimately wholly original, the CIRCUS agenda was an ambitious one and the WG has had a chequered history peppered with misunderstandings perpetrated by the very people who might have thought would give the WG their strongest support. The CIRCUS idea has been aired before, specifically at the University of Illinois at Urbana- Champaign, the MIT Media Lab (and its imitators), and a recent IEEE forum. However a near total change in participation, fuelled by natural migration and a switch to DG XIII, has resulted in the CIRCUS agenda being restarted on at least one occasion and a fairly regular questioning of the principles on whose elucidation we are engaged. While this is no bad thing in principle, in practice we haven’t learned anything new from these periodic bouts of self-examination other than a reinforcement of the values our goals. On the other hand it is evident that we have made progress and have moved on a long way from where we started. A recent experience of a workshop whose agenda appeared to be to form another version of CIRCUS, this time with an overwhelmingly technological (DG III) membership, demonstrates they have a CIRCUS-worth of work to do before they will have reached where we are now. (Foreword of CIRCUS for Beginners

Attentive Speaking. From Listener Feedback to Interactive Adaptation

Buschmeier H. Attentive Speaking. From Listener Feedback to Interactive Adaptation. Bielefeld: Universität Bielefeld; 2018.Dialogue is an interactive endeavour in which participants jointly pursue the goal of reaching understanding. Since participants enter the interaction with their individual conceptualisation of the world and their idiosyncratic way of using language, understanding cannot, in general, be reached by exchanging messages that are encoded when speaking and decoded when listening. Instead, speakers need to design their communicative acts in such a way that listeners are likely able to infer what is meant. Listeners, in turn, need to provide evidence of their understanding in such a way that speakers can infer whether their communicative acts were successful. This is often an interactive and iterative process in which speakers and listeners work towards understanding by jointly coordinating their communicative acts through feedback and adaptation. Taking part in this interactive process requires dialogue participants to have ‘interactional intelligence’. This conceptualisation of dialogue is rather uncommon in formal or technical approaches to dialogue modelling. This thesis argues that it may, nevertheless, be a promising research direction for these fields, because it de-emphasises raw language processing performance and focusses on fundamental interaction skills. Interactionally intelligent artificial conversational agents may thus be able to reach understanding with their interlocutors by drawing upon such competences. This will likely make them more robust, more understandable, more helpful, more effective, and more human-like. This thesis develops conceptual and computational models of interactional intelligence for artificial conversational agents that are limited to (1) the speaking role, and (2) evidence of understanding in form of communicative listener feedback (short but expressive verbal/vocal signals, such as ‘okay’, ‘mhm’ and ‘huh’, head gestures, and gaze). This thesis argues that such ‘attentive speaker agents’ need to be able (1) to probabilistically reason about, infer, and represent their interlocutors’ listening related mental states (e.g., their degree of understanding), based on their interlocutors’ feedback behaviour; (2) to interactively adapt their language and behaviour such that their interlocutors’ needs, derived from the attributed mental states, are taken into account; and (3) to decide when they need feedback from their interlocutors and how they can elicit it using behavioural cues.This thesis describes computational models for these three processes, their integration in an incremental behaviour generation architecture for embodied conversational agents, and a semi-autonomous interaction study in which the resulting attentive speaker agent is evaluated. The evaluation finds that the computational models of attentive speaking developed in this thesis enable conversational agents to interactively reach understanding with their human interlocutors (through feedback and adaptation) and that these interlocutors are willing to provide natural communicative listener feedback to such an attentive speaker agent. The thesis shows that computationally modelling interactional intelligence is generally feasible, and thereby raises many new research questions and engineering problems in the interdisciplinary fields of dialogue and artificial conversational agents

Learning in network organisations

This study addresses the nature of learning in organisations engaged in multiple outsourcing arrangements. It describes issues, problems and achievements for employees working with team members from other companies and nationalities. It finds that people learn through personal agency and relationship building, often overcoming significant barriers to communication and learning