The memory space: Exploring future uses of Web 2.0 and mobile internet through design interventions.

The QuVis Quantum Mechanics Visualization project aims to address challenges of quantum mechanics instruction through the development of interactive simulations for the learning and teaching of quantum mechanics. In this article, we describe evaluation of simulations focusing on two-level systems developed as part of the Institute of Physics Quantum Physics resources. Simulations are research-based and have been iteratively refined using student feedback in individual observation sessions and in-class trials. We give evidence that these simulations are helping students learn quantum mechanics concepts at both the introductory and advanced undergraduate level, and that students perceive simulations to be beneficial to their learning.Comment: 15 pages, 5 figures, 1 table; accepted for publication in the American Journal of Physic

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Reason Maintenance - Conceptual Framework

This paper describes the conceptual framework for reason maintenance developed as part of WP2

Inchcolm project

Inchcolm Project is part of an interdisciplinary research project which develops new ways of designing for the moving body across media, by combining aesthetics and design methods from contemporary performance practice and video games. As such, it brought a video game (Dear Esther, The Chinese Room, 2012) to life on a Scottish island (Inchcolm island in the Firth of Forth). During the two hour experience on Inchcolm the audience/players wander freely on the island encountering geo-tagged audio, live music, performers and installation spaces evocative of the game world, a playthrough of the game projected in the 12th century Inchcolm abbey, and an orchestral performance of the video game’s soundtrack (composed by Jessica Curry, arranged by Luci Holland and David Jamieson, performed by Mantra Collective)