Since the 1990s, art biennials have assumed a central place, alongside galleries and museums, in Europe's public infrastructure for visual arts. Biennials make strong claims regarding the radical potential of their artistic programmes. Their curators present them as cultural spaces within which the socio-political status quo can and should be challenged and disrupted. There is a dissonance between these claims and the other manifest functions of biennials: to produce new investment opportunities for art markets, and to support governmental strategies to boost tourism, regeneration, civic status and cultural participation. Torn between these roles, biennials struggle to deliver on their promises. This original research aims to identify ways in which biennials might change in order to realise their radical potential. It recognises that the current struggle is rooted in institutional conditions resistant to change. Focusing on the role of curators, it questions top-down, curator-centred approaches to the selection of artists and wider generation of content. Situating curators materially in organisations and institutions, and drawing upon my own professional experience, I first examine the current state of European biennials from 2010, compare their curatorial approaches and identify obstacles to change, including the institutionalisation of curators and their practices. Using a comparative case-study method, I will identify 3-5 European biennials that innovate and experiment with curatorial formats and processes in response to the issues above. Currently, I propose to think through the radical potential of biennials by employing two interrelated theories of cultural production: Deleuze and Guattari's "minor" art practice (1975), and Harney and Moten's "undercommons" (2013). Through analysis of primary and secondary material, including interviews and on-site ethnographic methods, I will explore and assess the potential of alternative curatorial approaches and emergent biennial models. My study will contribute to knowledge and impact on policy and management in the cultural and creative industries.

To create a cross-platform development capability and specifically in secure, high performance web application and smart device apps in order to grow market proposition.

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Hegel's philosophy, by its own nature as a pedagogical tool, sought to produce a new kind of subjectivity consistent with its goal of educating its readers in the 'Absolute Knowledge' of its philosophical system. In pursuit of their own versions of such knowledge, several of Hegel's most innovative followers searched for a suitably coherent 'post-systemic' subject of experience and practice. The core argument of my research is that the model of subjectivity proposed by Max Stirner (1806-1856), a former student of Hegel, best models the kind of subjectivity that the education of Hegelian philosophy ultimately produces. I argue that Stirner's theory individual subject as the 'creative nothing', whose emancipation consists in the fully self-conscious affirmation of their inherent flexibility and creative power-a power inseparable from the negativity at the core of individuality as such-exemplifies Hegel's theory of the plasticity of subjectivity and re-orients it towards emancipatory practice For Hegel, subjectivity is both inherently negative yet also inherently productive; and it is through an exposition of Hegel's theory of production, in conjunction with his theory of the plasticity of the subject in relation to this productive power of the negative, that I'll invoke Stirner as a model for the kind of subject that affirms itself to have this plasticity as well as this power. The reassertion of Stirnerian subjectivity as a necessary product of Hegel's system will have the consequence of calling into question the considerable absence of engagement with Stirner's thought in contemporary Hegel scholarship, and seeks to begin a conversation between the resurgent field of Stirner scholarship and contemporary Hegelian theory. This 'conversation' will attempt to fuse the conceptual analysis of Stirner's theory of the individual and its emancipation within Stirner scholarship with contemporary Hegel scholarship that seeks to draw on Hegel's system for emancipatory ends.

This proposal starts with the notion that, when considering future visual sensing technologies for next-generation Internet-of-Things surveillance, drone technology, and robotics, it is quickly becoming evident that sampling and processing raw pixels is going to be extremely inefficient in terms of energy consumption and reaction times. After all, the most efficient visual computing systems we know, i.e., biological vision and perception in mammals, do not use pixels and frame-based sampling. Therefore, IOSIRE argues that we need to explore the feasibility of advanced machine-to-machine (M2M) communications systems that directly capture, compress and transmit neuromorphically-sampled visual information to cloud computing services in order to produce content classification or retrieval results with extremely low power and low latency. IOSIRE aims to build on recently-devised hardware for neuromorphic sensing, a.k.a. dynamic vision sensors (DVS) or silicon retinas. Unlike conventional global-shutter (frame) based sensors, DVS cameras capture the on/off triggering corresponding to changes of reflectance in the observed scene. Remarkably, DVS cameras achieve this with (i) 10-fold reduction in power consumption (10-20 mW of power consumption instead of hundreds of milliwatts) and (ii) 100-fold increase in speed (e.g., when the events are rendered as video frames, 700-2000 frames per second can be achieved). In more detail, the IOSIRE project proposes a fundamentally new paradigm where the DVS sensing and processing produces a layered representation that can be used locally to derive actionable responses via edge processing, but select parts can also be transmitted to a server in the cloud in order to derive advanced analytics and services. The classes of services considered by IOSIRE require a scalable and hierarchical representation for multipurpose usage of DVS data, rather than a fixed representation suitable for an individual application (such as motion analysis or object detection). Indeed, this is the radical difference of IOSIRE from existing DVS approaches: instead of constraining applications to on-board processing, we propose layered data representations and adaptive M2M transmission frameworks for DVS data representations, which are mapped to each application's quality metrics, response times, and energy consumption limits, and will enable a wide range of services by selectively offloading the data to the cloud. The targeted breakthrough by IOSIRE is to provide a framework with extreme scalability: in comparison to conventional designs for visual data processing and transmission over M2M networks, and under comparable reconstruction, recognition or retrieval accuracy in applications, up to 100-fold decrease in energy consumption (and associated delay in transmission/reaction time) will be pursued. Such ground-breaking boosting of performance will be pursued via proof-of-concept designs and will influence the design of future commercial systems.