The elements of a computational infrastructure for social simulation

Applications of simulation modelling in social science domains are varied and increasingly widespread. The effective deployment of simulation models depends on access to diverse datasets, the use of analysis capabilities, the ability to visualize model outcomes and to capture, share and re-use simulations as evidence in research and policy-making. We describe three applications of e-social science that promote social simulation modelling, data management and visualization. An example is outlined in which the three components are brought together in a transport planning context. We discuss opportunities and benefits for the combination of these and other components into an e-infrastructure for social simulation and review recent progress towards the establishment of such an infrastructure

Super-forecasting the 'technological singularity' risks from artificial intelligence

This article investigates cybersecurity (and risk) in the context of ‘technological singularity’ from artificial intelligence. The investigation constructs multiple risk forecasts that are synthesised in a new framework for counteracting risks from artificial intelligence (AI) itself. In other words, the research in this article is not just concerned with securing a system, but also analysing how the system responds when (internal and external) failure(s) and compromise(s) occur. This is an important methodological principle because not all systems can be secured, and totally securing a system is not feasible. Thus, we need to construct algorithms that will enable systems to continue operating even when parts of the system have been compromised. Furthermore, the article forecasts emerging cyber-risks from the integration of AI in cybersecurity. Based on the forecasts, the article is concentrated on creating synergies between the existing literature, the data sources identified in the survey, and forecasts. The forecasts are used to increase the feasibility of the overall research and enable the development of novel methodologies that uses AI to defend from cyber risks. The methodology is focused on addressing the risk of AI attacks, as well as to forecast the value of AI in defence and in the prevention of AI rogue devices acting independently

The Combechem MQTT LEGO microscope: a grid enabled scientific apparatus demonstrator

Grid computing impacts directly on the experimental scientific laboratory in the areas of monitoring and remote control of experiments, and the storage, processing and dissemination of the resulting data. We highlight some of the issues in extending the use of an MQ Telemetry Transport (MQTT) broker from facilitating the remote monitoring of an experiment and its environment to the remote control of an apparatus. To demonstrate these techniques, an Intel-Play QX3 microscope has been "grid-enabled" using a combination of software to control the microscope imaging, and sample handling hardware built from LEGO Mindstorms. The whole system is controlled remotely by passing messages using an IBM WebSphere Message Broker. <br/

Collaborative information seeking with ant colony ranking in real-time

In this paper we propose a new ranking algorithm based on Swarm Intelligence, more specifically on the Ant Colony Optimization technique, to improve search engines’ performances and reduce the information overload by exploiting users’ collective behavior. We designed an online evaluation involving end users to test our algorithm in a real-world scenario dealing with informational queries. The development of a fully working prototype – based on the Wikipedia search engine – demonstrated promising preliminary results

Software development cultures and cooperation problems: a field study of the early stages of development of software for a scientific community

In earlier work, I identified a particular class of end-user developers, who include scientists and whom I term 'professional end-user developers', as being of especial interest. Here, I extend this work by articulating a culture of professional end-user development, and illustrating by means of a field-study how the influence of this culture causes cooperation problems in an inter-disciplinary team developing a software system for a scientific community. My analysis of the field study data is informed by some recent literature on multi-national work cultures. Whilst acknowledging that viewing a scientific development through a lens of software development culture does not give a full picture, I argue that it nonetheless provides deep insights