Abstract

Abstract
Following the proliferation of Augmented Reality technologies and applications in mobile devices it is becoming clear that AR techniques have matured and are ready to be used for large audiences. This poses several new multimedia interaction and usability problems that need to be identified and studied. AR problems are no longer exclusively about rendering superimposed virtual geometry or finding ways of performing GPS or computer vision registration. It is important to understand how to keep users engaged with AR and in what occasions it is suitable to use it. Additionally how should graphical user interfaces be designed so that the user can interact with AR elements while pointing a mobile device to a specific real world area? Finally what is limiting AR applications from reaching an even broader acceptance and usage level? This position paper identifies several interaction problems in today's multimedia AR applications, raising several pressing issues and proposes several research directions. Copyright

Abstract
A Shamanic Interface is a recent concept that posits that the acknowledgment of culture in gestural commands may contribute to richer and more powerful user interaction with abstract concepts and complexity, but has a lack of empirical validation. Hence, this paper presents a game developed as an empirical research tool for data collection and testing on shamanic interfaces. The game is a small maze where users use gestures to control a character to reach the end of each level. The control gestures performed by each user are captured with a Leap Motion controller and recognized through Hidden Markov Models. Three command sets were implemented: Portuguese cultural gestures, Dutch cultural gestures, and a generic set. This paper evaluates the game with different users to check its playability. We conclude that the game can be used as a research data-collection tool as is, but also acknowledge several playability-related improvement recommendations.

Abstract
Data analysis and monitoring is currently carried out within enterprises using Business Intelligence tools that are subject to major limitations (as outlined in the state of the art analysis that we perform). Effective visualization support is a very much needed feature in Big Data applications. In this paper we examine the visualisation requirements of a real world banking application, and identify generic visualisation tasks that are essential for doing effective analysis of a complex process that produces amazingly large amounts of data. The requirements for the visualization support that we propose are modelled using an application wireframe that acts a story-board. The effectiveness of the visualization facilities that we propose is demonstrated through their application to the Big Data banking use-case.

Abstract
The Global Positioning System (GPS) provides geolocation to a considerable number of applications in domains such as agriculture, commerce, transportation and tourism. Operational factors such as signal noise or the lack of direct vision from the receiver to the satellites, reduce the GPS geolocation accuracy. Urban canyons are a good example of an environment where continuous GPS signal reception may fail. For some applications, the lack of geolocation accuracy, even if happening for a short period of time, may lead to undesired results. For instance, consider the damages caused by the failure of the geolocation system in a city tour-bus transportation that shows location-sensitive data (historical/cultural data, publicity) in its screens as it passes by a location. This work presents an innovative approach for keeping geolocation accurate in mobile systems that rely mostly on GPS, by using computer vision to help providing geolocation data when the GPS signal becomes temporarily low or even unavailable. Captured frames of the landscape surrounding the mobile system are analysed in real-time by a computer vision algorithm, trying to match it with a set of geo-referenced images in a preconfigured database. When a match is found, it is assumed that the mobile system current location is close to the GPS location of the corresponding matched point. We tested this approach several times, in a real world scenario, and the results achieved evidence that geolocation can effectively be improved for scenarios where GPS signal stops being available.

Abstract
Incentivized Sustainable Mobility is a conceptual business model which involves four stakeholders: citizens, municipalities, commerce and mobility services. A platform named ISUMO (Incentivized Sustainable Mobility) provides technological support to this business model, integrating a set of metaservices that unifies the existing ICTs of transportation plus a unique patented QR-based (Quick Response) low-cost charging device for electric vehicles. Essentially, the system tracks and registers citizens' transportation activities (anonymously and voluntarily) and evaluates each through a scoring system while their ecological footprint is calculated. Afterwards, citizens are able to exchange their accumulated points for discount QR coupons, to be redeemed in the associated commerce in order to purchase their products or services. The breakthrough of this business model is that it enhances awareness of sustainable mobility practices, increasing their attractiveness as perceived by the stakeholders with diverse benefits; citizens (and indirectly, the municipalities) initiate a new consumption pattern of coupons culture linked to sustainable mobility, the urban economy is stimulated, and the use of mobility services grows, providing a new business opportunity regarding electric vehicles. It is expected that continuous exploration of the model and implementation will contribute to sustainable social and economic development aiming at CO2 emissions reduction, headline targets of the Europe 2020 strategy.