843 research outputs found

    Mill, Intuitions, and Normativity

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    It is the purpose of this paper to offer an account of Mill’s metaethics, byexpanding on clues given recently by Dale Miller, and previously by JohnSkorupski, to the effect that, when it comes to the foundations of hisphilosophy, Mill might share more with the intuitionists than we areaccustomed to think. Common wisdom holds that Mill had no time forthe normativity of intuitions. I wish to dispute, or at least temper, thisdogma, by claiming that Mill’s attitude towards intuitions is far morecomplex and ambivalent than is generally thought. The investigation,then, centres on the question of whether, for Mill, intuitions carrynormative warrant: whether, in itself, the fact that a belief is intuitionalprovides reason to think that belief a warranted one. I argue that,according to Mill, our belief in the reliability of inductive moves andapparent memories, as well as the desirability of pleasure, is vindicated bysomething akin to intuition. Although his endorsement of the normativityof these intuitions might seem to be in tension with the arguments heoffers against the ‘intuitionist school’, this tension is only apparent

    Match made in heaven.

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    In this article, the interface between biotechnology, nanotechnology and microelectronics is discussed. In particular, how proteins or other active organic agents may be bound onto silicon wafers. The article also discusses the applications of such systems, particularly in medicine

    Innovative approaches to fuel-air mixing and combustion in airbreathing hypersonic engines.

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    This paper describes some innovative methods for achieving enhanced fuel-air mixing and combustion in Scramjet-like spaceplane engines. A multimodal approach to the problem is discussed; this involves using several concurrent methods of forced mixing. The paper concentrates on Electromagnetic Activation (EMA) and Electrostatic Attraction as suitable techniques for this purpose - although several other potential methods are also discussed. Previously published empirical data is used to draw conclusions about the likely effectiveness of the system and possible engine topologies are outlined

    Mill on the Primacy of Practical Reason

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    In this article, I wish to argue that J.S. Mill holds that theoretical reason is subordinate to practical reason. Ultimately, this amounts to the claim that the norms of theoretical reason – those rules governing how we ought to believe – are grounded in considerations of utility. I begin, in Section 1, by offering an outline of Mill’s account of the ‘Art of Life’ (the body of rules governing how we should act), before turning in Section 2, to Mill’s account of the ‘Art of Thinking’ (the body of rules governing how we should believe). In Section 3, I suggest that, for Mill, the Art of Thinking is subordinate to the Art of Life, and that in an important sense, therefore, theoretical reason is subordinate to practical reason

    The synthesis of artificial neural networks using single string evolutionary techniques.

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    The research presented in this thesis is concerned with optimising the structure of Artificial Neural Networks. These techniques are based on computer modelling of biological evolution or foetal development. They are known as Evolutionary, Genetic or Embryological methods. Specifically, Embryological techniques are used to grow Artificial Neural Network topologies. The Embryological Algorithm is an alternative to the popular Genetic Algorithm, which is widely used to achieve similar results. The algorithm grows in the sense that the network structure is added to incrementally and thus changes from a simple form to a more complex form. This is unlike the Genetic Algorithm, which causes the structure of the network to evolve in an unstructured or random way. The thesis outlines the following original work: The operation of the Embryological Algorithm is described and compared with the Genetic Algorithm. The results of an exhaustive literature search in the subject area are reported. The growth strategies which may be used to evolve Artificial Neural Network structure are listed. These growth strategies are integrated into an algorithm for network growth. Experimental results obtained from using such a system are described and there is a discussion of the applications of the approach. Consideration is given of the advantages and disadvantages of this technique and suggestions are made for future work in the area. A new learning algorithm based on Taguchi methods is also described. The report concludes that the method of incremental growth is a useful and powerful technique for defining neural network structures and is more efficient than its alternatives. Recommendations are also made with regard to the types of network to which this approach is best suited. Finally, the report contains a discussion of two important aspects of Genetic or Evolutionary techniques related to the above. These are Modular networks (and their synthesis) and the functionality of the network itself

    How integrative modelling can break down disciplinary silos

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    This paper has been published in a peer-reviewed journal as: Kragt, M.E., Robson, B.J. & Macleod, C.J.A. (2013) Modellers’ roles in structuring integrative research projects. Environmental Modelling & Software, 39(1): 322-330. DOI: 10.1016/j.envsoft.2012.06.015Environmental modelling, Interdisciplinary research, Transdisciplinarity, Integration, Research Methods/ Statistical Methods, Q57, Y80, Z19,

    Does the use of specialist palliative care services modify the effect of socioeconomic status on place of death? A systematic review

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    © SAGE Publications. Background: Cancer patients in lower socioeconomic groups are significantly less likely to die at home and experience more barriers to access to palliative care. It is unclear whether receiving palliative care may mediate the effect of socioeconomic status on place of death. Aim: This review examines whether and how use of specialist palliative care may modify the effect of socioeconomic status on place of death. Design: A systematic review was conducted. Eligible papers were selected and the quality appraised by two independent reviewers. Data were synthesised using a narrative approach. Data sources: MEDLINE, Embase, CINAHL, PsycINFO and Web of Knowledge were searched (1997-2013). Bibliographies were scanned and experts contacted. Papers were included if they reported the effect of both socioeconomic status and use of specialist palliative care on place of death for adult cancer patients. Results: Nine studies were included. All study subjects had received specialist palliative care. With regard to place of death, socioeconomic status was found to have (1) no effect in seven studies and (2) an effect in one study. Furthermore, one study found that the effect of socioeconomic status on place of death was only significant when patients received standard specialist palliative care. When patients received more intense care adapted to their needs, the effect of socioeconomic status on place of death was no longer seen. Conclusion: There is some evidence to suggest that use of specialist palliative care may modify the effect of socioeconomic status on place of death

    Artificial biochemical networks: a different connectionist paradigm.

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    Connectionist models are usually based on artificial neural networks. However, there is another route towards parallel distributed processing. This is by considering the origins of the intelligence displayed by the single celled organisms known as protoctists. Such intelligence arises by means of the biochemical interactions within the animal. An artificial model of this might therefore be termed an artificial biochemical network or ABN. This paper describes the attributes of such networks and illustrates their abilities in pattern recognition problems and in generating time-varying signals of a type which can be used in many control tasks. The flexibility of the system is explained using legged robots as an example. The networks are trained using back propagation and evolutionary algorithms such as genetic algorithms
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