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Firewalls are important perimeter security mechanisms that imple-ment an organisation's network security requirements and can be notoriously difficult to configure correctly. Given their widespread use, it is crucial that network administrators have tools to translate their security requirements into firewall configuration rules and ensure that these rules are consistent with each other. In this paper we propose an approach to firewall policy specification and analysis that uses a formal framework for argumentation based preference reasoning. By allowing administrators to define network abstractions (e.g. subnets, protocols etc) security requirements can be specified in a declarative manner using high-level terms. Also it is possible to specify preferences to express the importance of one requirement over another. The use of a formal framework means that the security requirements defined can be automatically analysed for inconsistencies and firewall configurations can be automatically generated. We demonstrate that the technique allows any inconsistency property, including those identified in previous research, to be specified and automatically checked and the use of an argumentation reasoning framework provides administrators with information regarding the causes of the inconsistency.

Dans le cadre de l'intérêt porté aux impacts des investissements chinois en Afrique sub-saharienne (ASS), cet article porte sur l'engagement de ces pays africains dans un partenariat avec des grandes entreprises d'Etat chinoises qui investissent dans les secteurs d'infrastructures et de ressources naturelles. Après avoir démontré l'ampleur des différents types d'investissements chinois, l'attention porte sur les caractéristiques propres à ces grandes entreprises publiques. Ces investissements chinois sont étroitement liés à l'aide et au commerce. L’article conclut que les pays d’ASS devraient adopter une réponse également intégrée et ciblée vis-à-vis les investisseurs chinois ainsi qu’aux autres investisseurs à grande échelle qui cherchent à exploiter leurs ressources afin de maximiser les opportunités qui leur sont offertes du fait des dotations en ressources naturelles du continent.European Journal of Development Research (2009) 21, 551–569. doi:10.1057/ejdr.2009.24

The LOFT mission concept is one of four candidates selected by ESA for the M3 launch opportunity as Medium Size missions of the Cosmic Vision programme. The launch window is currently planned for between 2022 and 2024. LOFT is designed to exploit the diagnostics of rapid X-ray flux and spectral variability that directly probe the motion of matter down to distances very close to black holes and neutron stars, as well as the physical state of ultra-dense matter. These primary science goals will be addressed by a payload composed of a Large Area Detector (LAD) and a Wide Field Monitor (WFM). The LAD is a collimated (<1 degree field of view) experiment operating in the energy range 2-50 keV, with a 10 m^2 peak effective area and an energy resolution of 260 eV at 6 keV. The WFM will operate in the same energy range as the LAD, enabling simultaneous monitoring of a few-steradian wide field of view, with an angular resolution of <5 arcmin. The LAD and WFM experiments will allow us to investigate variability from submillisecond QPO's to year-long transient outbursts. In this paper we report the current status of the project. Proceedings of SPIE, Vol. 8443, Paper No. 8443-85, 2012

The Southeast Asian region is experiencing some of the world’s highest rates of deforestation and forest degradation, the principle drivers of which are agricultural expansion and wood extraction in combination with an increased incidence of fire. Recent changes in fire regimes in Southeast Asia are indicative of increased human-causd forest disturbance, but El Niño–Southern Oscillation (ENSO) events also play a role in exacerbating fire occurrence and severity. Fires are now occurring on a much more extensive scale - in part because forest margins are at greater risk of fire as a result of disturbance through logging activities, but also as a result of rapid, large-scale forest clearance for the establish-ment of plantations. Millions of hectares have been deforested and drained to make way for oil palm and pulpwood trees, and many plantation companies, particularly in Indonesia, have employed fire as a cheap land clearance tool; uncontrolled fires have entered adjacent forests or plantation estates, and burnt both the forest biomass and, in peatland areas, underlying peat. Forest fires cause changes to forest structure, biodiversity, soil and hydrology. Repeated fires over successive or every few years lead to a progressive decline in the number of primary forest species. Fire leads to reduction in both aboveground and below ground organic carbon stocks and also changes carbon cycling patterns. In non-peatland areas, losses of carbon from fire affected forest vegetation exceed greatly soil carbon losses, but on carbon-rich substrates, e.g. peat, combustion losses can be considerable. Peatland fires make a major contribution to atmospheric emissions of greenhouse gases, fine particular matter and aerosols and thus contribute to climate change as well as presenting a problem for human health. The scale of emissions is unlikely to reduce in coming decades, since climate modelling studies have predicted that parts of this region will experience lower rainfall in future and greater seasonality. Protecting the rainforests of this region from further fire disasters should be at the top of the global environmental agenda, with highest priority given to peatland areas.

Involving the collaboration of researchers from Classics, Geography and Archaeological Computing, and supported by funding from the AHRC, HESTIA (the Herodotus Encoded Space-Text-Imaging Archive) aims to enrich contemporary discussions of space by developing an innovative methodology for the study of an ancient narrative, Herodotus’s Histories. Using the latest digital technology in combination with close textual study, we investigate the geographical concepts through which Herodotus describes the conflict between Greeks and Persians. Our findings nuance the customary topographical vision of an east versus west polarity by drawing attention to the topological network culture that criss-crosses the two, and develop the means of bringing that world to a mass audience via the internet. In this paper we discuss three main aspects to the project: the data capture of place-names in Herodotus; their visualization and dissemination using the web-mapping technologies of GIS, Google Earth and Timemap; and the interrogation of the relationships that Herodotus draws between different geographical concepts using the digital resources at our disposal. Our concern will be to set out in some detail the digital basis to our methodology and the technologies that we have been exploiting, as well as the problems that we have encountered, in the hope of contributing not only to a more complex picture of space in Herodotus but also to a basis for future digital projects across the Humanities that spatially visualize large text-based corpora. With this in mind we end with a brief discussion of some of the ways in which this study is being developed, with assistance from research grants from the Google Digital Humanities Awards Program and JISC.

The potential of open data as a resource for driving citizen-led urban innovation relies not only on a suitable technical infrastructure but also on the skills and knowledge of the citizens themselves. In this chapter, we describe how a smart city project in Milton Keynes, UK, is supporting multiple stages of citizen innovation, from ideation to citizen-led smart city projects. The Our MK initiative provides support and funding to help citizens develop their ideas about making their communities more sustainable into reality. This approach encounters challenges when engaging with citizens in identifying and implementing data-driven solutions to urban problems. The majority of citizens have little practical experience with the types of data sets that might be available or possess the appropriate skills for their analysis and utilisation for addressing urban issues or finding novel ways to hack their city. We go on to describe the Urban Data School, which aims to offer a long-term solution to this problem by providing teaching resources around urban data sets aimed at raising the standard of data literacy amongst future generations. Lesson resources that form part of the Urban Data School have been piloted in one primary and three secondary schools in Milton Keynes. This work has demonstrated that with the appropriate support, even young children can begin to develop the skills necessary to work with large complex data sets. Through our two approaches, we illustrate some of the barriers to citizen participation in urban innovation and detail our solutions to overcoming those barriers. Post-print / Final draft

We present early results from our multi-wavelength follow-up campaigns of the AKARI Deep Fields at the North and South Ecliptic Poles. We summarize our campaigns in this poster paper, and present three early outcomes. (a) Our AAOmega optical spectroscopy of the Deep Field South at the AAT has observed over 550 different targets, and our preliminary local luminosity function at 90 ?m from the first four hours of data is in good agreement with the predictions from Serjeant & Harrison (2005). (b) Our GMRT 610 MHz imaging in the Deep Field North has reached ?30 ?Jy RMS, making this among the deepest images at this frequency. Our 610 MHz source counts at >200 ?Jy are the deepest ever derived at this frequency. (c) Comparing our GMRT data with our 1.4 GHz WSRT data, we have found two examples of radio-loud AGN that may have more than one epoch of activity.

Multilevel principal components analysis (mPCA) has previously been shown to provide a simple and straightforward method of forming point distribution models that can be used in (active) shape models. Here we extend the mPCA approach to model image texture as well as shape. As a test case, we consider a set of (2D frontal) facial images from a group of 80 Finnish subjects (34 male; 46 female) with two different facial expressions (smiling and neutral) per subject. Shape (in terms of landmark points) and image texture are considered separately in this initial analysis. Three-level models are constructed that contain levels for biological sex, “within-subject” variation (i.e., facial expression), and “between-subject” variation (i.e., all other sources of variation). By considering eigenvalues, we find that the order of importance as sources of variation for facial shape is: facial expression (47.5%), between-subject variations (45.1%), and then biological sex (7.4%). By contrast, the order for image texture is: between-subject variations (55.5%), facial expression (37.1%), and then biological sex (7.4%). The major modes for the facial expression level of the mPCA models clearly reflect changes in increased mouth size and increased prominence of cheeks during smiling for both shape and texture. Even subtle effects such as changes to eyes and nose shape during smile are seen clearly. The major mode for the biological sex level of the mPCA models similarly relates clearly to changes between male and female. Model fits yield “scores” for each principal component that show strong clustering for both shape and texture by biological sex and facial expression at appropriate levels of the model. We conclude that mPCA correctly decomposes sources of variation due to biological sex and facial expression (etc.) and that it provides a reliable method of forming models of both shape and image texture.