Abstract
This paper presents a combination of optimization and data mining techniques to address the surgery scheduling problem. In this approach, we first develop a model to predict the duration of the surgeries using a data mining algorithm. The prediction model outcomes are then used by a mathematical optimization model to schedule surgeries in an optimal way. In this paper, we present the results of using three different data mining algorithms to predict the duration of surgeries and compare them with the estimates made by surgeons. The results obtained by the data mining models show an improvement in estimation accuracy of 36%.We also compare the schedules generated by the optimization model based on the estimates made by the prediction models against reality. Our approach enables an increase in the number of surgeries performed in the operating theater, thus allowing a reduction on the average waiting time for surgery and a reduction in the overtime and undertime per surgery performed. These results indicate that the proposed approach can help the hospital improve significantly the efficiency of resource usage and increase the service levels. © Springer-Verlag 2012.

Abstract
Rekindles can represent a high burden on wildland fire suppression resources, but despite the relevance of this phenomenon in Portugal, related research is still scarce. Seeking to contribute to address this gap, the purpose of this study was to organize and provide an overview of the problem of rekindles in Portugal, and to verify whether evidence exists that the high proportion of rekindles in Portugal is related to the double duty of Portuguese firefighters to perform initial attack and mop-up operations. Our study included informal meetings, formal recorded interviews, dispatch centre visits, actual rekindle observation, and an analysis of the National Forest Authority database. From the study of genealogies of rekindles, we concluded that 17.2% additional forest fires (rekindles in successive generations) had their origin in only 7.4% of primary fires. Through linear regression analysis, we found that their proportions increase in days with more occurrences, preliminarily supporting the hypothesis of premature abandonment of mop-up operations, as a result from the pressure to immediately attack starting fires by the same crews. A more detailed analysis of two representative districts highlighted specific organizational and natural challenges to successful mop-up efforts and provided further evidence of the hazardousness of rekindles. © 2012 WIT Press.

Abstract
This paper provides a review of the literature on applications of the Driving forces, Pressure, State, Impact, Response (DPSIR) framework to fisheries. The interpretation given to each DPSIR category differs in existing studies, and as a result the indicators used to support fisheries management also vary considerably. This impairs comparisons concerning the state of different fishery systems, and does not provide a common base of knowledge concerning potential management measures that can be adopted in a given context. This paper clarifies the interpretation of each DPSIR category and proposes a set of indicators that can be applied in fishery contexts. The set of indicators proposed is also classified according to sustainability dimensions. It is argued that organising the indicators according to the DPSIR framework and sustainability dimensions (ecologic, economic, social and governance) is a positive contribution to serve as a guideline for future applications to adopt standardized indicators and improve fisheries management.

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
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.