Exploring the democratic potential of online social networking: The scope and limitations of e-participation

Copyright © 2012 by the Association for Information Systems.The availability and promise of social networking technologies with their perceived open philosophy has increasingly inspired citizens around the world to participate in political activity on the Web. Recent examples range from opposing public policies, such as government funding cuts, to organizing revolutionary social movements, such as those in the Middle East and North Africa. Although online spaces create remarkable opportunities for various forms of political action, there are concerns over the power of existing institutions to control and even censor such interaction spaces. The objective of this article is to draw together different insights on the online engagement phenomenon, highlighting both its potential and limitations as a mechanism for fostering democratic debate and influencing policy making. We examine recent examples from Europe, the Middle East and Latin America. Finally, we summarize the implications of our work and outline directions for further research

Superfluidity of Dense 4^4He in Vycor

We calculate properties of a model of $^4$He in Vycor using the Path Integral Monte Carlo method. We find that $^4$He forms a distinct layered structure with a highly localized first layer, a disordered second layer with some atoms delocalized and able to give rise to the observed superfluid response, and higher layers nearly perfect crystals. The addition of a single $^3$He atom was enough to bring down the total superfluidity by blocking the exchange in the second layer. Our results are consistent with the persistent liquid layer model to explain the observations. Such a model may be relevant to the experiments on bulk solid $^4$He, if there is a fine network of grain boundaries in those systems.Comment: 4 pages, 4 figure

Dynamics of Learning with Restricted Training Sets I: General Theory

We study the dynamics of supervised learning in layered neural networks, in the regime where the size $p$ of the training set is proportional to the number $N$ of inputs. Here the local fields are no longer described by Gaussian probability distributions and the learning dynamics is of a spin-glass nature, with the composition of the training set playing the role of quenched disorder. We show how dynamical replica theory can be used to predict the evolution of macroscopic observables, including the two relevant performance measures (training error and generalization error), incorporating the old formalism developed for complete training sets in the limit $\alpha=p/N\to\infty$ as a special case. For simplicity we restrict ourselves in this paper to single-layer networks and realizable tasks.Comment: 39 pages, LaTe

Estimation of Kumaraswamy Distribution Parameters Using the Principle of Maximum Entropy

This paper proposes using maximum entropy approach to estimate the parameters of the Kumaraswamy distribution subject to moment constraints. Kumaraswamy [7] introduced the double pounded probability density function which was originally used to model hydrological phenomena. It was mentioned that this probability density function is applicable to bounded natural phenomena which have values on two sides. The distribution share several properties with the beta distribution and it has the extra advantages that is possesses a closed form distribution function, but it remained unknown to most statisticians until it was developed by Jones [6] as a beta-type distribution with some tractability advantages in particular as it has fairly simple quantile function and it has explicit formula for L-Moment. Using the principle of maximum entropy to propose new estimators for the Kumaraswamy parameters and compared with maximum likelihood and Bayesian estimation methods. A simulation study is performed to investigate the performance of the estimators in terms of their mean square errors and their efficiency

Solutions for certain classes of Riccati differential equation

We derive some analytic closed-form solutions for a class of Riccati equation y'(x)-\lambda_0(x)y(x)\pm y^2(x)=\pm s_0(x), where \lambda_0(x), s_0(x) are C^{\infty}-functions. We show that if \delta_n=\lambda_n s_{n-1}-\lambda_{n-1}s_n=0, where \lambda_{n}= \lambda_{n-1}^\prime+s_{n-1}+\lambda_0\lambda_{n-1} and s_{n}=s_{n-1}^\prime+s_0\lambda_{k-1}, n=1,2,..., then The Riccati equation has a solution given by y(x)=\mp s_{n-1}(x)/\lambda_{n-1}(x). Extension to the generalized Riccati equation y'(x)+P(x)y(x)+Q(x)y^2(x)=R(x) is also investigated.Comment: 10 page