Hamilton's theory of turns revisited

We present a new approach to Hamilton's theory of turns for the groups SO(3) and SU(2) which renders their properties, in particular their composition law, nearly trivial and immediately evident upon inspection. We show that the entire construction can be based on binary rotations rather than mirror reflections.Comment: 7 pages, 4 figure

Prophylactic Neutrality, Oppression, and the Reverse Pascal's Wager

In Beyond Neutrality, George Sher criticises the idea that state neutrality between competing conceptions of the good helps protect society from oppression. While he is correct that some governments are non-neutral without being oppressive, I argue that those governments may be neutral at the core of their foundations. The possibility of non-neutrality leading to oppression is further explored; some conceptions of the good would favour oppression while others would not. While it is possible that a non-neutral state may avoid oppression, it is argued that the risks are so great that it is better to bet on government being neutral, thereby minimizing the possibility of oppression

Potential errors in using one anemometer to characterize the wind power over an entire rotor disk

Wind data collected at four levels on a 90-m tower in a prospective wind farm area are used to evaluate how well the 10-m wind speed data with and without intermittent vertical profile measurements compare with the 90-m tower data. If a standard, or even predictable, wind speed profile existed, there would be no need for a large, expensive tower. This cost differential becomes even more significant if several towers are needed to study a prospective wind farm

Development of a 50 kW fluid transpiration arc solar simulator Final report

Development of 50 kW fluid transpiration arc solar simulato

Choosing Products in Social Networks

We study the consequences of adopting products by agents who form a social network. To this end we use the threshold model introduced in Apt and Markakis, arXiv:1105.2434, in which the nodes influenced by their neighbours can adopt one out of several alternatives, and associate with such each social network a strategic game between the agents. The possibility of not choosing any product results in two special types of (pure) Nash equilibria. We show that such games may have no Nash equilibrium and that determining the existence of a Nash equilibrium, also of a special type, is NP-complete. The situation changes when the underlying graph of the social network is a DAG, a simple cycle, or has no source nodes. For these three classes we determine the complexity of establishing whether a (special type of) Nash equilibrium exists. We also clarify for these categories of games the status and the complexity of the finite improvement property (FIP). Further, we introduce a new property of the uniform FIP which is satisfied when the underlying graph is a simple cycle, but determining it is co-NP-hard in the general case and also when the underlying graph has no source nodes. The latter complexity results also hold for verifying the property of being a weakly acyclic game.Comment: 15 pages. Appeared in Proc. of the 8th International Workshop on Internet and Network Economics (WINE 2012), Lecture Notes in Computer Science 7695, Springer, pp. 100-11

Connecting the latent multinomial

Link et al. (2010) define a general framework for analyzing capture-recapture data with potential misidentifications. In this framework, the observed vector of counts, $y$, is considered as a linear function of a vector of latent counts, $x$, such that $y = A x$, with $x$ assumed to follow a multinomial distribution conditional on the model parameters, $\theta$. Bayesian methods are then applied by sampling from the joint posterior distribution of both $x$ and $\theta$. In particular, Link et al. (2010) propose a Metropolis-Hastings algorithm to sample from the full conditional distribution of $x$, where new proposals are generated by sequentially adding elements from a basis of the null space (kernel) of $A$. We consider this algorithm and show that using elements from a simple basis for the kernel of $A$ may not produce an irreducible Markov chain. Instead, we require a Markov basis, as defined by Diaconis and Sturmfels (1998). We illustrate the importance of Markov bases with three capture-recapture examples. We prove that a specific lattice basis is a Markov basis for a class of models including the original model considered by Link et al. (2010) and confirm that the specific basis used by Link et al. (2010) for their example with two sampling occasions is a Markov basis. The constructive nature of our proof provides an immediate method to obtain a Markov basis for any model in this class