168,888 research outputs found

    Adaptive architecture and personal data

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    Through sensors carried by people and sensors embedded in the environment, personal data is being processed to try to understand activity patterns and people’s internal states in the context of human-building interaction. This data is used to actuate adaptive buildings to make them more comfortable, convenient, and accessible or information rich. In a series of envisioning workshops, we queried the future relationships between people, personal data and the built environment, when there are no technical limits to the availability of personal data to buildings. Our analysis of created designs and user experience fictions allows us to contribute a systematic exposition of the emerging design space for adaptive architecture that draws on personal data. This is being situated within the context of the new European information privacy legislation, the EU General Data Protection Regulation 2016. Drawing on the tension space analysis method, we conclude with the illustration of the tensions in the temporal, spatial, and inhabitation-related relationships of personal data and adaptive buildings, re-usable for the navigation of the emerging, complex issues by future designers

    Adaptive architecture: Regulating human building interaction

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    In this paper we explore regulatory, technical and interactional implications of Adaptive Architecture, a novel trend emerging in the built environment. We provide a comprehensive description of the emergence and history of the term, with reference to the current state of the art and policy foundations supporting it e.g. smart city initiatives and building regulations. As Adaptive Architecture is underpinned by the Internet of Things (IoT), we are interested in how regulatory and surveillance issues posed by the IoT manifest in buildings too. To support our analysis, we utilise a prominent concept from architecture, Stuart Brand’s Shearing Layers model, which describes the different physical layers of a building and how they relate to temporal change. To ground our analysis, we use three cases of Adaptive Architecture, namely an IoT device (Nest Smart Cam IQ); an Adaptive Architecture research prototype, (ExoBuilding); and a commercial deployment (the Edge). In bringing together Shearing Layers, Adaptive Architecture and the challenges therein, we frame our analysis under 5 key themes. These are guided by emerging information privacy and security regulations. We explore the issues Adaptive Architecture needs to face for: A – ‘Physical & information security’; B – ‘Establishing responsibility’; C – ‘occupant rights over flows, collection, use & control of personal data’; D- ‘Visibility of Emotions and Bodies’; & E – ‘Surveillance of Everyday Routine Activities’. We conclude by summarising key challenges for Adaptive Architecture, regulation and the future of human building interaction

    PACMAS: A Personalized, Adaptive, and Cooperative MultiAgent System Architecture

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    In this paper, a generic architecture, designed to support the implementation of applications aimed at managing information among different and heterogeneous sources, is presented. Information is filtered and organized according to personal interests explicitly stated by the user. User pro- files are improved and refined throughout time by suitable adaptation techniques. The overall architecture has been called PACMAS, being a support for implementing Personalized, Adaptive, and Cooperative MultiAgent Systems. PACMAS agents are autonomous and flexible, and can be made personal, adaptive and cooperative, depending on the given application. The peculiarities of the architecture are highlighted by illustrating three relevant case studies focused on giving a support to undergraduate and graduate students, on predicting protein secondary structure, and on classifying newspaper articles, respectively

    Robustness-Driven Resilience Evaluation of Self-Adaptive Software Systems

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    An increasingly important requirement for certain classes of software-intensive systems is the ability to self-adapt their structure and behavior at run-time when reacting to changes that may occur to the system, its environment, or its goals. A major challenge related to self-adaptive software systems is the ability to provide assurances of their resilience when facing changes. Since in these systems, the components that act as controllers of a target system incorporate highly complex software, there is the need to analyze the impact that controller failures might have on the services delivered by the system. In this paper, we present a novel approach for evaluating the resilience of self-adaptive software systems by applying robustness testing techniques to the controller to uncover failures that can affect system resilience. The approach for evaluating resilience, which is based on probabilistic model checking, quantifies the probability of satisfaction of system properties when the target system is subject to controller failures. The feasibility of the proposed approach is evaluated in the context of an industrial middleware system used to monitor and manage highly populated networks of devices, which was implemented using the Rainbow framework for architecture-based self-adaptation

    Automated user modeling for personalized digital libraries

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    Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information

    User-centred design of flexible hypermedia for a mobile guide: Reflections on the hyperaudio experience

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    A user-centred design approach involves end-users from the very beginning. Considering users at the early stages compels designers to think in terms of utility and usability and helps develop the system on what is actually needed. This paper discusses the case of HyperAudio, a context-sensitive adaptive and mobile guide to museums developed in the late 90s. User requirements were collected via a survey to understand visitors’ profiles and visit styles in Natural Science museums. The knowledge acquired supported the specification of system requirements, helping defining user model, data structure and adaptive behaviour of the system. User requirements guided the design decisions on what could be implemented by using simple adaptable triggers and what instead needed more sophisticated adaptive techniques, a fundamental choice when all the computation must be done on a PDA. Graphical and interactive environments for developing and testing complex adaptive systems are discussed as a further step towards an iterative design that considers the user interaction a central point. The paper discusses how such an environment allows designers and developers to experiment with different system’s behaviours and to widely test it under realistic conditions by simulation of the actual context evolving over time. The understanding gained in HyperAudio is then considered in the perspective of the developments that followed that first experience: our findings seem still valid despite the passed time

    Towards a competency model for adaptive assessment to support lifelong learning

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    Adaptive assessment provides efficient and personalised routes to establishing the proficiencies of learners. We can envisage a future in which learners are able to maintain and expose their competency profile to multiple services, throughout their life, which will use the competency information in the model to personalise assessment. Current competency standards tend to over simplify the representation of competency and the knowledge domain. This paper presents a competency model for evaluating learned capability by considering achieved competencies to support adaptive assessment for lifelong learning. This model provides a multidimensional view of competencies and provides for interoperability between systems as the learner progresses through life. The proposed competency model is being developed and implemented in the JISC-funded Placement Learning and Assessment Toolkit (mPLAT) project at the University of Southampton. This project which takes a Service-Oriented approach will contribute to the JISC community by adding mobile assessment tools to the E-framework

    A self-regulated learning approach : a mobile context-aware and adaptive learning schedule (mCALS) tool

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    Self-regulated students are able to create and maximize opportunities they have for studying or learning. We combine this learning approach with our Mobile Context-aware and Adaptive Learning Schedule (mCALS) tool which will create and enhance opportunities for students to study or learn in different locations. The learning schedule is used for two purposes, a) to help students organize their work and facilitate time management, and b) for capturing the users’ activities which can be retrieved and translated as learning contexts later by our tool. These contexts are then used as a basis for selecting appropriate learning materials for the students. Using a learning schedule to capture and retrieve contexts is a novel approach in the context-awareness mobile learning field. In this paper, we present the conceptual model and preliminary architecture of our mCALS tool, as well as our research questions and methodology for evaluating it. The learning materials we intend to use for our tool will be Java for novice programmers. We decided that this would be appropriate because large amounts of time and motivation are necessary to learn an object-oriented programming language such as Java, and we are currently seeking ways to facilitate this for novice programmers
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