According to the World Health Organisation, three to five million individuals are infected by influenza, and around 250,000 to 500,000 people die of this infectious disease worldwide. Influenza epidemics pose a serious public health threat. Moreover, graver dangers are encountered with influenza subtypes against which there is little or no preexisting human immunity. Such subtypes of influenza have the potential to cause devastating epidemics. Thus, enhancing surveillance systems for the purpose of detecting influenza epidemics in an early stage can quicken (...) response times and save millions of lives. This paper presents three adapting intelligence models: support vector machine regression, artificial neural network using particle swarm optimisation, and our intelligent time series to predict influenza epidemics. The novelty of the current study is that it proposes a new intelligent model to predict influenza outbreaks. The INTS model combines clustering with a time series model to enhance the prediction of influenza outbreaks. The innovation of our proposed model integrates the results obtained from the existing weighted exponential smoothing model with centroids obtained from clustering. We developed a surveillance system for influenza epidemics using Google search queries. The current research is based on a weighted version of the Center for Disease Control and Prevention influenza-like illness activity level obtained from the Center for Disease Control and Prevention data, as well as query data obtained from the Goggle search engine in the USA. The influenza-like illness data was collected from January 4, 2009, to December 27, 2015, stretching across a total time span of 312 weeks. Google Correlate was used to select search queries related to influenza epidemics. In total, 100 search queries were obtained from Google Correlate, 10 of which were better and more relevant search queries selected in this study. The model was evaluated using online Google search queries collected from Google Correlate. Standard measure performance MSE, RMSE, and MAE were employed to estimate the results of the proposed model. The empirical results of the INTS model showed MSE = 0.003, RMSE = 0.036, and MAE = 0.0185, indicating that the errors of the proposed model are very limited. A comparative model of predicting results between the INTS model, alternative Google Flu Trend, and autoregression with Google search data is also presented. The proposed model outperformed the existing models. (shrink)

First published in 2002. Routledge is an imprint of Taylor & Francis, an informa company.

First published in 2002. Routledge is an imprint of Taylor & Francis, an informa company.

Epistemologists have not usually had much to say about believing ‘in’, though ever since Plato's time they have been interested in believing ‘that’. Students of religion, on the other hand, have been greatly concerned with belief ‘in’, and many of them, I think, would maintain that it is something quite different from belief ‘that’. Surely belief ‘in’ is an attitude to a person, whether human or divine, while belief ‘that’ is just an attitude to a proposition? Could any difference be (...) more obvious than this? And if we over-look it, shall we not be led into a quite mistaken analysis of religious belief, at any rate if it is religious belief of the theistic sort? On this view belief ‘in’ is not a propositional attitude at all. (shrink)

First published in 2002. Routledge is an imprint of Taylor & Francis, an informa company.

May I first say, Mr Chairman, that I regard it as a great honour to have been invited to take part in this Conference? I speak to you as a philosopher who happens to be interested both in religion and in psychical research. But I am afraid I am going to discuss some questions which it is ‘not done’ to talk about.

In ordinary life everyone assumes that he has a great deal of knowledge about other minds or persons. This assumption has naturally aroused the curiosity of philosophers; though perhaps they have not been as curious about it as they ought to have been, for they have devoted many volumes to our consciousness of the material world, but very few to our consciousness of one another. It was thought at one time that each of us derives his knowledge of other minds (...) from the observation of other human organisms. I observe that there are a number of bodies which resemble my own fairly closely in their shape, size, and manner of movement; I conclude by analogy that each of these bodies is animated by a. (shrink)

I am very grateful to Professor R. W. Sleeper for his critical comments on my article, as also for the kind way in which he has expressed them. I should now like to make a few comments on his comments. May I first say that I have no objection to being metaphysical? I do not like the word ‘metaphysics’ very much, and wish that we could find a less provocative one. But still, I do think that the difference between the (...) reducible and the irreducible belief-in is a difference which there really is . Moreover, I fully admit that when we believe in God we are making a factual claim. It is, of course, a factual claim of rather a special kind. If it is a fact that there is a supreme Being, ‘The Lord of All’, this is not just one fact among others. It is not quite like the fact that there is a stormy north-westerly wind this morning. One could not just give a list of facts and add at the end, ‘There is also another fact which I had forgotten to mention: there is a God’. All the same, this factual claim, like others, does need to be justified; and how is it to be justified? I am afraid that the brief hint which I offered elsewhere on this subject is indeed ‘not good enough’ as it stands . To be even half good enough, it needs much more elaboration, and I agree that there is much force in Mr Gunderson's criticisms. (shrink)

All sciences have epistemic assumptions, a language for expressing their theories or models, and symbols that reference observables that can be measured. In most sciences the language in which their models are expressed are not the focus of their attention, although the choice of language is often crucial for the model. On the contrary, biosemiotics, by definition, cannot escape focusing on the symbol–matter relationship. Symbol systems first controlled material construction at the origin of life. At this molecular level it is (...) only in the context of open-ended evolvability that symbol–matter systems and their functions can be objectively defined. Symbols are energy-degenerate structures not determined by laws that act locally as special boundary conditions or constraints on law-based energy-dependent matter in living systems. While this partial description holds for all symbol systems, cultural languages are much too complex to be adequately described only at the molecular level. Genetic language and cultural languages have common basic requirements, but there are many significant differences in their structures and functions. (shrink)