The challenge of citizen participation for democracy

The paper starts from the observation that the forms of citizen participation have changed considerably from what could be observed in the 1950s and 1960s. Election turn-outs are falling, grass-roots activities of citizens are on the rise and political commentaries in different forms are proliferating on the Internet. How can we conceptualise modern democratic systems and forms of participation? How helpful is democracy theory for this endeavour? The paper revisits classic and post-modern models of democracy and makes an effort to conceptualise and classify modern practices of citizen participation on the basis of categories derived from democracy theory. Democracy theory should also be of help in providing an answer to the question of how democratic instruments of interactive governance actually are. Criteria for the evaluation of these instruments and their impact on policy-making will be derived from theorizing on democracy and some proposals will be made for an operationalisation of these criteria

Beyond bureaucracy and entrepreneurialism: Examining the multiple discursive codes informing the work, careers and subjectivities of management graduates

This paper examines how discursive codes and demands associated with ‘bureaucratic and entrepreneurial regimes’ of work and career organization shape the work, careers and subjectivities of management graduates. The study is based on an analysis of 30 narratives of management professionals who graduated from an Austrian business school in the early 1970s or 2000s. Its insights suggest that variegated discursive codes manifest in the graduates’ articulated professional practices and subjectivities, thereby challenging established assumptions regarding the organization of work and careers. While the practices and subjectivities of the 1970s graduates are often informed by codes and demands ascribed to ‘entrepreneurialism’, those of the 2000s graduates are infused with several codes commonly portrayed as ‘bureaucratic’

An Evaluation of Camera Pose Methods for an Augmented Reality System: Application to Teaching Industrial Robots

International audienceIn automotive industry, industrial robots are widely used in production lines for many tasks such as welding, painting or assembly. Their use requires, from users, both a good manipulation and robot control. Recently, new tools have been developed to realize fast and accurate trajectories in many production sectors by using the real prototype of vehicle or a generalized design within a virtual simulation platform. However, many issues could be considered in these cases: the delay between the design of the vehicle and its production is often important, moreover, the virtual modeling presents a non realistic aspect of the real robot and vehicle, so this factor could introduce localization inacurracies in performing trajectories. Our work is registered as a part of TRI project (Teleteaching Industrial Robots) which aims to realize a demonstrator showing the interaction of industrial robots with virtual components and allowing to train users to perform successfully their tasks on a virtual representation of a production entity. In this project we make use of Augmented Reality (AR) techniques to overlay virtual objects onto the real world in order to enhance the user's perception and interaction while performing a specific industrial task. The idea is to allow the real robot to teach trajectories of an automotive task thanks to vehicle virtual model. The pose accuracy is prerequisite of our application since it allows a reliable teaching of the real trajectory. Therefore, we survey some vision-based pose computation algorithms and present a method that offers increased robustness and accuracy in the context of real-time AR tracking. Our aim is to determine the performance of these pose estimation methods in term of errors and distance evaluation. The evaluation of the pose estimation methods was obtained using a series of tests and an experimental protocol. The analysis of results shows the performance of algorithms in term of accuracy, stability and convergence