Reproducing violence: Rihanna, Chris Brown and the aestheticisation of the Ciudad Juarez Femicides.

When Kate and Laura Mulleavy of Rodarte worked with MAC to create their Autumn/Winter 2010 makeup collection and based their ideas on the murdered women of Ciudad Juarez, there was a public and industry outcry which led to the withdrawal of cosmetics with names such as ‘Factory’ ‘Juarez’ and ‘Ghost Town’. Rodarte tapped into the borderland mythologies of Juarez and crated an illusory fantasy world which sought to simultaneously obliterate and venerate the dead women. One eyeshadow, ‘Bordertown’, appears to look like chunks of rotting flesh streaked with blood. The models for their catwalk show had hollow blackened eyes, green-white pallor and lips that had been bloodlessly ‘lip-erased’ with a product specifically designed for the purpose. In Spanish, maquillar is to make up, to assemble. The women in the factories are asked to repeat simple mechanical operations thousands of times a day to make up the products which will be sold by global corporations. At the same time their images are being assembled, made up and aestheticized to create a cosmetic erasure of the crimes which they are subject to. When two American women and a global company make profit from this dangerous cosmetic erasure in order to sell products, the borders between bodies, countries, art and crime become leaky through the act and the illusion of symbiosis between the women of Ciudad Juarez and the products they inspired is threatened by the haunting of exploitation. Since then, the situation has become more complex. Chris Brown got a neck tattoo, based, he says, on the promotional material produced by MAC for the Rodarte sisters campaign. The image, which is of a skull, bears a striking resemblance to the police photographs of his ex, and now current, girlfriend, superstar Rihanna. The controversy over gendered violence, race and exploitation, begun by Rodarte and MAC, came back, haunting, once again. This paper seeks to address these connections, and ask what happens when domestic violence collides with globalism, fashion and murder.

Novel information sharing syntax for data sharing between police and community partners, using role-based security.

The exchange of information between the police and community partners forms a central aspect of effective community service provision. In the context of policing, a robust and timely communications mechanism is required between police agencies and community partner domains, including: Primary healthcare (such as a Family Physician or a General Practitioner); Secondary healthcare (such as hospitals); Social Services; Education; and Fire and Rescue services. Investigations into high-profile cases such as the Victoria Climbié murder in 2000, the murders of Holly Wells and Jessica Chapman in 2002, and, more recently, the death of baby Peter Connelly through child abuse in 2007, highlight the requirement for a robust information-sharing framework. This paper presents a novel syntax that supports information-sharing requests, within strict data-sharing policy definitions. Such requests may form the basis for any information-sharing agreement that can exist between the police and their community partners. It defines a role-based architecture, with partner domains, with a syntax for the effective and efficient information sharing, using SPoC (Single Point-of-Contact) agents to control in-formation exchange. The application of policy definitions using rules within these SPoCs is inspired by network firewall rules and thus define information exchange permissions. These rules can be imple-mented by software filtering agents that act as information gateways between partner domains. Roles are exposed from each domain to give the rights to exchange information as defined within the policy definition. This work involves collaboration with the Scottish Police, as part of the Scottish Institute for Policing Research (SIPR), and aims to improve the safety of individuals by reducing risks to the community using enhanced information-sharing mechanisms.

On Clonal Selection.

Clonal selection has been a dominant theme in many immune-inspired algorithms applied to machine learning and optimisation. We examine existing clonal selections algorithms for learning from a theoertical and empirical perspective and assert that the widely accepted computational interpretation of clonal selection is compromised both algorithmically andbiologically. We suggest a more capable abstraction of the clonal selection principle grounded in probabilistic estimation and approximation and demonstrate how it addresses some of the shortcomings in existing algorithms. We further show that by recasting black-box optimisation as a learning problem, the same abstraction may be re-employed; thereby taking steps toward unifying the clonal selection principle and distinguishing it from natural selection.