New electronic tablet devices are often referred to as either saviours of newspapers or killers of traditional print media. These crude statements are based on a naive concept of media substitution and an overestimation of the actual use of new media for news consumption. It is much more likely that substitution will be marginal, and that the potential is much more in giving existing readers more options while attacking new users. Publishers should treat tablet devices as options, concentrating on issues like business models, free, freemium, sponsored and paid content, DRM, in-app payment models, partnerships, user-generated content, design and interface options. Academic research on the use of tablets is not yet available as these devices are not available on a massive scale, only appearing on the market since the spring of 2010, but experiences by many publishers of newspapers and magazines already provide us with enough material to map possibilities and no-go areas for publishers of news content
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Green spaces play an important role in urban areas. We study the accessibility of green urban areas by combining open data sets about green with population size data. We develop a mathematical model to define the population density of a green area and calculate the available green space depending on the location. To this end, we do not only consider walking distance to and size of the green area, but also take into account the local population size. Our model quantifies how the available green space depends on the location in the city, such that heavily populated areas have a small amount of green available, even when closely located to a green area.
The complexity of analysing dynamical systems often lies in the difficulty to monitor each of their dynamic properties. In this article, we use qualitative models to present an exhaustive way of representing every possible state of a given system, and combine it with Bayesian networks to integrate quantitative information and reasoning under uncertainty. The result is a combined model able to give explanations relying on expert knowledge to predict the behaviour of a system. We illustrate our approach with a deterministic model to show how the combination is done, then extend this model to integrate uncertainty and demonstrate its benefits
