5,496 research outputs found

    Modelling the nature and consequences of accidental radioactive releases to the atmosphere

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    Imperial Users onl

    It’s a long way to Monte-Carlo: probabilistic display in GPS navigation

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    We present a mobile, GPS-based multimodal navigation system, equipped with inertial control that allows users to explore and navigate through an augmented physical space, incorporating and displaying the uncertainty resulting from inaccurate sensing and unknown user intentions. The system propagates uncertainty appropriately via Monte Carlo sampling and predicts at a user-controllable time horizon. Control of the Monte Carlo exploration is entirely tilt-based. The system output is displayed both visually and in audio. Audio is rendered via granular synthesis to accurately display the probability of the user reaching targets in the space. We also demonstrate the use of uncertain prediction in a trajectory following task, where a section of music is modulated according to the changing predictions of user position with respect to the target trajectory. We show that appropriate display of the full distribution of potential future users positions with respect to sites-of-interest can improve the quality of interaction over a simplistic interpretation of the sensed data

    Show me the way to Monte Carlo: density-based trajectory navigation

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    We demonstrate the use of uncertain prediction in a system for pedestrian navigation via audio with a combination of Global Positioning System data, a music player, inertial sensing, magnetic bearing data and Monte Carlo sampling for a density following task, where a listener’s music is modulated according to the changing predictions of user position with respect to a target density, in this case a trajectory or path. We show that this system enables eyes-free navigation around set trajectories or paths unfamiliar to the user and demonstrate that the system may be used effectively for varying trajectory width and context

    On-line energy services for smart homes

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    The EC funded 'Smart Homes' project commenced in 2001 as a 3 year programme. The primary objective is to establish Internet-based energy services and test these within field trials in Sweden, Greece, the Czech Republic and the UK. The tasks include the prototyping and testing of energy services for citizens and professionals, and the establishment of cable and wireless approaches to Internet connection. The implementations are based on residential gateway, or 'e-box', technology. Users, for example utilities, citizens, local authority energy managers and health care providers, can access the information through standard Web browsers and, depending on the particular energy service, may transmit information or control requests back to the originating homes. This paper sets out the overall structure of the SmartHomes system and reports on progress to date

    The ‘Chaldee Manuscript’, William Hone, and late Georgian religious parody

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    This article analyses Blackwood's notorious ‘Translation from an Ancient Chaldee Manuscript’ (1817), contextualising the satire in the light of religious parody, ancient and modern – but in particular the latter – and arguing that there were specific reasons why a post-Napoleonic magazine might have used this particular form at this particular moment. It examines the publication, publicity, and purposes of the ‘Chaldee’, a key part of William Blackwood's reboot of his failing magazine in October 1817, and the contemporary religious parody of the radical pressman William Hone, which led, three times, to his prosecution and acquittal, and which directly informed that most famous part of Blackwood's succès de scandale

    A strategic study of energy efficient and hybrid energy system options for a multi-family building in Korea

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    This study is to identify performance of energy efficiency measures and to match low-carbon and renewable energy (RE) systems supplies to demands in the context of multi-family residential buildings in Korea. An approach to the evaluation of the hybrid energy systems was investigated, including consideration of heat and power demand profiles, energy system combinations, building design options and strategies for matching supply to demand. The approach is encapsulated within an integrated software environment. Building energy simulation technology was exploited to make virtual energy use data. Low-carbon and RE system modelling techniques were used to predict energy supply profiles. A series of demand/supply matching-based analyses were made to identify the effect of energy efficient demand measures (e.g. roof-top gardens, innovative underfloor heating system) and evaluate the capacity utilisation factor from the hybrid energy systems. On the basis of performance information obtained at the conceptual design stage, the design team can pinpoint the most energy efficient demand/supply combination, and consequently, maximise the impact of hybrid energy systems adoption

    Variability in wrist-tilt accelerometer based gesture interfaces

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    In this paper we describe a study that examines human performance in a tilt control targeting task on a PDA. A three-degree of freedom accelerometer attached to the base of the PDA allows users to navigate to the targets by tilting their wrist in different directions. Post hoc analysis of performance data has been used to classify the ease of targeting and variability of movement in the different directions. The results show that there is an increase in variability of motions upwards from the centre, compared to downwards motions. Also the variability in the x axis component of the motion was greater than that in the y axis. This information can be used to guide designers as to the ease of various relative motions, and can be used to reshape the dynamics of the interaction to make each direction equally easy to achieve

    Practical applications of data mining in plant monitoring and diagnostics

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    Using available expert knowledge in conjunction with a structured process of data mining, characteristics observed in captured condition monitoring data, representing characteristics of plant operation may be understood, explained and quantified. Knowledge and understanding of satisfactory and unsatisfactory plant condition can be gained and made explicit from the analysis of data observations and subsequently used to form the basis of condition assessment and diagnostic rules/models implemented in decision support systems supporting plant maintenance. This paper proposes a data mining method for the analysis of condition monitoring data, and demonstrates this method in its discovery of useful knowledge from trip coil data captured from a population of in-service distribution circuit breakers and empirical UHF data captured from laboratory experiments simulating partial discharge defects typically found in HV transformers. This discovered knowledge then forms the basis of two separate decision support systems for the condition assessment/defect clasification of these respective plant items
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