2,868 research outputs found

    Ghent University-Department of Textiles: annual report 2013

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    The patterning of finance/security : a designerly walkthrough of challenger banking apps

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    Culture is being ‘appified’. Diverse, pre-existing everyday activities are being redesigned so they happen with and through apps. While apps are often encountered as equivalent icons in apps stores or digital devices, the processes of appification – that is, the actions required to turn something into an app – vary significantly. In this article, we offer a comparative analysis of a number of ‘challenger’ banking apps in the United Kingdom. As a retail service, banking is highly regulated and banks must take steps to identify and verify their customers before entering a retail relationship. Once established, this ‘secured’ financial identity underpins a lot of everyday economic activity. Adopting the method of the walkthrough analysis, we study the specific ways these processes of identifying and verifying the identity of the customer (now the user) occur through user onboarding. We argue that banking apps provide a unique way of binding the user to an identity, one that combines the affordances of smart phones with the techniques, knowledge and patterns of user experience design. With the appification of banking, we see new processes of security folded into the everyday experience of apps. Our analysis shows how these binding identities are achieved through what we refer to as the patterning of finance/security. This patterning is significant, moreover, given its availability for wider circulation beyond the context of retail banking apps

    An application of augmented MDA for the extended healthcare enterprise

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    Mobile health systems extend the enterprise computing system of the healthcare provider by bringing services to the patient any time and anywhere. We propose a methodology for the development of such extended enterprise computing systems which applies a model-driven design and development approach augmented with formal validation and verification to address quality and correctness and to support model transformation. At the University of Twente we develop context aware m-health systems based on Body Area Networks (BANs). A set of deployed BANs are supported by a server. We refer to this distributed system as a BAN System. Development of such distributed m-health systems requires a sound software engineering approach and this is what we target with the proposed methodology. The methodology is illustrated with reference to modelling activities targeted at real implementations. BAN implementations are being trialled in a number of clinical settings including epilepsy management and management of chronic pain

    The Challenge of Energy Management – Status-Quo and Perspectives for Reference Models

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    Energy management is one of the great challenges of the industry in the next years. Energy becomes more and more to a critical resource. Until now, enterprises need to implement energy management system with nearly no guidance. In the following paper we present the foundation of a reference model-based method that serves for setting up energy management systems in various industrial sectors. The goal is to support reduction emission and cost reduction as well as certification needs. In contrast to previous approaches, this approach enables a model-based certification and allows an automation of activities of the process of supervision of the consumption of energy and the appropriate reengineering of business processes

    The Healthgrid White Paper

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    Digital Forensics AI: Evaluating, Standardizing and Optimizing Digital Evidence Mining Techniques

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    The impact of AI on numerous sectors of our society and its successes over the years indicate that it can assist in resolving a variety of complex digital forensics investigative problems. Forensics analysis can make use of machine learning models’ pattern detection and recognition capabilities to uncover hidden evidence in digital artifacts that would have been missed if conducted manually. Numerous works have proposed ways for applying AI to digital forensics; nevertheless, scepticism regarding the opacity of AI has impeded the domain’s adequate formalization and standardization. We present three critical instruments necessary for the development of sound machine-driven digital forensics methodologies in this paper. We cover various methods for evaluating, standardizing, and optimizing techniques applicable to artificial intelligence models used in digital forensics. Additionally, we describe several applications of these instruments in digital forensics, emphasizing their strengths and weaknesses that may be critical to the methods’ admissibility in a judicial process
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