9,125 research outputs found

    An Ipswichian Palaeo-shoreline in Holderness

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    Previous research has identified a possible palaeo-shoreline extending across the Holderness region of Yorkshire. A 3D modelling project has revealed the extent of this feature under the Quaternary sediments across the entire area. The model also reveals the general palaeo-landscape of the area. This poster illustrates the first full 3D visualisation of this buried shoreline and proposes further investigative work that could be undertake

    Representation in Westminster in the 1990s : The ghost of Edmund Burke

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    Why are 'trustee' notions of representation still invoked in the UK House of Commons in the 1990s? In answering this question this article analyses the premises of Burkean theory and the arguments that these premises are of little relevance in the late twentieth century. Despite these dismissals of trusteeship, Burkean ideas are still articulated in the Commons some 200 years after they were first voiced. The idea of trusteeship can prove extremely useful to justify the actions of representatives when those actions conflict with constituency 'opinion', party policy or the wishes of interest groups. Examples of the occasions when Burkean notions have been invoked in the 1990s are provided

    Meditation Matters: Replies to the Anti-McMindfulness Bandwagon!

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    A critical reply to the anti-mindfulness critics in the collection, who oppose the popular secularized adoption of mindfulness on various grounds (it is not Buddhism, it is Buddhism, it is a tool of neo-capitalist exploitation, etc.), I argue that mindfulness is a quality of consciousness, opposite mindlessness, that may be cultivated through practice, and is almost always beneficial to those who cultivate it

    Clinical practice highlights in Clinical Neurophysiology in 2015 (January–March)

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    ATONING FOR KILLING: THE PRACTICE OF PENANCE AND THE PERCEPTION OF BLOODSHED AMONG THE EARLY MEDIEVAL IRISH, FIFTH TO NINTH CENTURY.

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    From the introduction of Christianity into Ireland in the fifth century to the arrival of the Vikings in the ninth, the attitudes of the Irish Church towards bloodshed and violence changed considerably. The moral code of pacifism and non-violence, especially towards other Christians, advocated by the Christian Churches came into direct confrontation with the violent necessities of secular life when the Roman Empire adopted the new faith as its state religion. Further difficulties arose when the Roman Empire gave way to Germanic kingdoms, and when the Christian faith began to make its way out to lands unconquered by Rome, such as Ireland; challenged by cultures in which honour and violence were part of the social fabric, and by the idea that victory in battle demonstrated divine favour, the Church had to both integrate itself into these new lands and try to draw them closer to the Christian ideal. Penance for the sins committed in life could be undertaken, but it was an arduous and humiliating process, such that many did not seek redemption until near death, an attitude which did not rest easy with the Church. The monastic system of penance, fixed in term and confessed in private, became available to the laity in the British Isles, a seismic shift which would allow a layman a new avenue to atone for sins of bloodshed, from murder to killing in war. It has, however, been questioned as to whether such penance was widely available to the laity as a whole or only to a specific group from among them. This thesis will explore how this changing attitude towards violence within the Irish Church demonstrates that this new form of penitential practice was indeed available to the whole laity through examining the development in nuance concerning the various sins of bloodshed across not only the Irish Penitentials, but hagiography, canon law, secular law, narratives, and other texts

    David Burke at Bloomingdale\u27s

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    Evolving Machine Morality Strategies through Multiagent Simulations

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    There is a general consensus among robotics researchers that the world of the future will be filled with autonomous and semi-autonomous machines. There is less of a consensus, though, on the best approach to instilling a sense of \u27machine morality\u27 in these systems so that they will be able to have effective interactions with humans in an increasingly complex world. In my talk, we take a brief look at some existing approaches to computational ethics, and then describe work we\u27ve undertaken creating multiagent simulations involving moral decision-making during strategic interactions. In these simulations, agents make choices about whether to cooperate with each other based on each agent\u27s weighting of five moral attributes (reciprocity, harm avoidance, loyalty, authority, purity). Our hope is that watching how these populations evolve over time can provide insights into how large numbers of distributed, autonomous systems might be programmed with respect to moral decision-making and behavior.https://pdxscholar.library.pdx.edu/systems_science_seminar_series/1066/thumbnail.jp

    Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping

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    The lack of reliable data in developing countries is a major obstacle to sustainable development, food security, and disaster relief. Poverty data, for example, is typically scarce, sparse in coverage, and labor-intensive to obtain. Remote sensing data such as high-resolution satellite imagery, on the other hand, is becoming increasingly available and inexpensive. Unfortunately, such data is highly unstructured and currently no techniques exist to automatically extract useful insights to inform policy decisions and help direct humanitarian efforts. We propose a novel machine learning approach to extract large-scale socioeconomic indicators from high-resolution satellite imagery. The main challenge is that training data is very scarce, making it difficult to apply modern techniques such as Convolutional Neural Networks (CNN). We therefore propose a transfer learning approach where nighttime light intensities are used as a data-rich proxy. We train a fully convolutional CNN model to predict nighttime lights from daytime imagery, simultaneously learning features that are useful for poverty prediction. The model learns filters identifying different terrains and man-made structures, including roads, buildings, and farmlands, without any supervision beyond nighttime lights. We demonstrate that these learned features are highly informative for poverty mapping, even approaching the predictive performance of survey data collected in the field.Comment: In Proc. 30th AAAI Conference on Artificial Intelligenc
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