ARTHUR: A Collaborative Augmented Environment for Architectural Design and Urban Planning

Projects in the area of architectural design and urban planning typically engage several architects as well as experts from other professions. While the design and review meetings thus often involve a large number of cooperating participants, the actual design is still done by the individuals in the time in between those meetings using desktop PCs and CAD applications. A real collaborative approach to architectural design and urban planning is often limited to early paper-based sketches.In order to overcome these limitations, we designed and realized the ARTHUR system, an Augmented Reality (AR) enhanced round table to support complex design and planning decisions for architects. WhileAR has been applied to this area earlier, our approach does not try to replace the use of CAD systems but rather integrates them seamlessly into the collaborative AR environment. The approach is enhanced by intuitiveinteraction mechanisms that can be easily con-figured for different application scenarios.

Towards an Open Source Framework for Collaborative Problem-Based Learning Environments

This paper presents our research works in the domain of Collaborative Environments centred on Problem Based Learning (PBL) and taking advantage of existing Electronic Documents. We first present the modelling and engineering problems that we want to address; then we discuss technological issues of such a research particularly the use of OpenUSS and of the Enterprise Java Open Source Architecture (EJOSA) to implement such collaborative PBL environments.

Faking or Convincing: Why Do Some Advertising Campaigns Win Creativity Awards?

Since the Sarbanes-Oxley Act was passed in 2002, it has become commonplace in the advertising industry to use creativity-award-show prizes instead of gross income figures to attract new customers. Therefore, achieving a top creativity ranking and winning creativity awards have become high priorities in the advertising industry. Agencies and marketers have always wondered what elements in the advertising creation process would lead to the winning of creativity awards. Although this debate has been dominated by pure speculation about the success of different routines, approaches and strategies in winning creativity awards, for the first time our study delivers an empirical insight into the key drivers of creativity award success. We investigate what strategies and which elements of an advertising campaign are truly likely to lead to winning the maximum number of creativity awards. Using a sample of 108 campaigns, we identify factors that influence campaign success at international advertising award shows. We identify innovativeness and the integration of multiple channels as the key drivers of creativity award success. In contrast to industry beliefs, meaningful or personally connecting approaches do not seem to generate a significant benefit in terms of winning creativity awards. Finally, our data suggest that the use of so-called “fake campaigns” to win more creativity awards does not prove to be effective.

Method of collaborative detection of autonomous transport vehicles based on laser rangefinder data

To master changing performance demands, autonomous transport vehicles are deployed to make inhouse material flow applications more flexible. The socalled cellular transport system consists of a multitude of small scale transport vehicles which shall be able to form a swarm. Therefore the vehicles need to detect each other, exchange information amongst each other and sense their environment. By provision of peripherally acquired information of other transport entities, more convenient decisions can be made in terms of navigation and collision avoidance. This paper is a contribution to collective utilization of sensor data in the swarm of cellular transport vehicles.