Abstract
In BSc/MSc engineering programmes at Faculty of Engineering of the University of Porto (FEUP), the need to provide students with teamwork experiences close to a real world environment was identified as an important issue. A new group-formation method that aims to provide an enriching teamwork experience is proposed. Students are asked to answer a questionnaire to evaluate their teamwork profiles and are assigned to groups by an algorithm aiming to achieve maximum diversity within groups and homogeneity among groups. The profile diversity/complementarity within a group is an important factor to promote members' commitment and coordination in order to achieve the proposed goals. The proposed method is compared to a standard self-selection method for three engineering programmes in three academic years. The results show that, with the new method, there are a higher number of medium ranked groups which surpass the expectation and that, contrary to some students' beliefs, the method does not have a negative impact on the overall final marks. © 2009 SEFI.

Abstract
Schematic Maps are mainly used for depicting transportation networks. They are generated through a schematization process where irrelevant details are eliminated and important details are emphasized. This process, being manually performed by teams of expert designers, is expensive and time consuming. Such manual execution is unsuitable for the production of schematic maps for location-based services or on-demand schematic maps, as near real-time and user-centered properties are needed. This work proposes GeneX, a framework that can support the automated generation of schematic maps. The framework and a new algorithms developed were able to completely eliminate erroneous map point placement, and to decrease by 33% the contention for map point placement, producing schematic maps without human intervention in soft real time.

Abstract
In recent years, mass adoption of increasingly powerful mobile devices and ubiquitous communication networks have paved the way to smart environments. Such environments allow for the collection of user and environment data with the final goal to improve users' experience. In this context a number of opportunities and challenges are presented to Human Computer Interaction. This poster explores Quality of Experience, a subjective aspect of interaction, informally defined as the degree to which a system meets users' expectations. Furthermore, a mobile application was developed for the collection of user and environment data and delivery of personalised services in the context of Public Transport. This application will be used in a real-world environment, to further investigate the factors that have an influence on User eXperience, as well as the delivery of relevant services with the potential to enhance users' journeys while in transit.

Abstract
Location-Based Services(LBS) are information services which are available through mobile devices inside a mobile network and can take advantage of the location of the mobile device. With the majority of the world population living in urban areas and using complex transportation systems, they can be used to assist people to use the public transportation systems more effectively and efficiently. This research aims to contribute to the improvement of LBS through the use of a new kind of a schematic map, called spider map that brings together geographic information in particular in its central location, or hub, with a schematic information of the overall transport network originating in the hub, including for instance relevant stops and their locations. These maps present an innovative layout that includes context information relevant for the users. They can be used to increase LBS user satisfaction and therefore increase the intention to use Public Transportation Services.

Abstract
In recent years the mass adoption of mobile devices and increasingly ubiquitous connectivity have contributed to a radical change in the way people interact with computer systems. Moreover cloud computing infrastructures have paved the way for the development of smart systems in such settings, whose goal is to provide a service to enhance user experience based on environment and user sensed data. In this context, there is a clear disconnection between the two streams that flow continuously between user and cloud-based systems. On the one hand, user- and environment-generated data is being, for the most part, disregarded by service providers. On the other hand, services offered do not address users' specific needs and preferences. In addition, service discovery is a cognitive demanding process and it may have detrimental consequences in user experience. In this paper we propose a user-centric framework that addresses the disconnection between these two streams: Cloud2Bubble. The framework facilitates the design and development of smart systems. It aims at leveraging existing technology, such as environment sensors and personal devices, to aggregate localised user-related data - defined as a bubble - into the cloud. This aggregation later supports the delivery of personalised services, contextually relevant to users. The delivery of services with such characteristics has the potential to enhance quality of experience and influence user behaviour. A first iteration of the platform was developed and an evaluation in a simulated environment was performed with encouraging results. Thus, the platform will be further expanded for instantiation and evaluation in the context of urban public transports. We intend to investigate the effects of relevant service delivery in terms of enhancement of quality of experience and influencing user behaviour. The delivery of a service with these characteristics presents benefits for both users and service providers. © 2012 ACM.

Abstract
This paper describes an application of genetic algorithms to the bus driver scheduling problem. The application of genetic algorithms extends the traditional approach of Set Covering/Set Partitioning formulations, allowing the simultaneous consideration of several complex criteria. The genetic algorithm is integrated in a DSS but can be used as a very interactive tool or a stand-alone application. It incorporates the user's knowledge in a quite natural way and produces solutions that are almost directly implemented by the transport companies in their operational planning processes. Computational results with airline and bus crew scheduling problems from real world companies are presented and discussed.