Abstract
While video surveillance systems are spreading everywhere, extracting meaningful information from what they are recording is still prohibitively expensive. There is a major effort under way in order to make this process economical by including an intelligent software that eases the burden of the system. In this paper, we introduce an incremental learning framework to classify parallel data streams generated in a multi-camera surveillance scenario. The framework exploits active learning strategies in order to interact wisely with operators to address various problems that exist in such non-stationary environments, such as concept drift and concept evolution. If we look at the problem as mining parallel streams, the framework can address learning from uneven parallel streams applying a class-based ensemble, a problem that has not been addressed before. Favourable results indicate the success of the framework.

Abstract
This paper summarizes existing systems and research on information transport services, and proposes a hypothetic scenario for future travellers using public transport. Increased distributed intelligence in pervasive mobile smart devices and in sensor networks in public transport vehicles is enabling a new approach for enhancing the experience of public transport customers. Such environment could be modelled through a distributed multi-agent service system. This paper presents advanced information services already available on such environments, in particular the MOVE-ME smartphone application, and indicates a possible service environment where people's feedback may benefit all transport service stakeholders. Mobile computing and crowdsourcing are key enablers for enhancing user experience in the transport services, and also for enhancing overall public transport services. Better experience leads to increased usage of shared mobility modes, and therefore to more sustainable cities in the future. Concerns about data security, and anonymity of travellers will need to be adequately addressed in the future scenarios presented.

Abstract
With an ever increasing number of vehicles traveling the roads, traffic problems such as congestions and increased travel times became a hot topic in the research community, and several approaches have been proposed to improve the performance of the traffic networks. This paper introduces the Inverted Ant Colony Optimization (IACO) algorithm, a variation of the classic Ant Colony algorithm that inverts its logic by converting the attraction of ants towards pheromones into a repulsion effect. IACO is then used in a decentralized traffic management system, where drivers become ants that deposit pheromones on the followed paths; they are then repelled by the pheromone scent, thus avoiding congested roads, and distributing the traffic through the network. Using SUMO (Simulation of Urban MObility), several experiments were conducted to compare the effects of using IACO with a shortest time algorithm in artificial and real world scenarios - using the map of a real city, and corresponding traffic data. The effect of the behavior caused by this algorithm is a decrease in traffic density in widely used roads, leading to improvements on the traffic network at a local and global level, decreasing trip time for drivers that adhere to the suggestions made by IACO as well as for those who do not. Considering different degrees of adhesion to the algorithm, IACO has significant advantages over the shortest time algorithm, improving overall network performance by decreasing trip times for both IACO-compliant vehicles (up to 84%) and remaining vehicles (up to 71%). Thus, it benefits individual drivers, promoting the adoption of IACO, and also the global road network. Furthermore, fuel consumption and CO2 emissions from both vehicle types decrease significantly when using IACO (up to 49%).

Abstract
Serious Games is a field of research that has evolved substantially with valuable contributions to many application domains and areas. Patients often consider traditional rehabilitation approaches to be repetitive and boring, making it difficult for them to maintain their ongoing interest and to assure the completion of the treatment program. This paper reviews Serious Games and the natural and multimodal user interfaces for the health rehabilitation domain. Specifically, it details a framework for the development of Serious Games that integrates a rich set of features that can be used to improve the designed games with direct benefits to the rehabilitation process. Highlighted features include natural and multimodal interaction, social skills (collaboration and competitiveness) and progress monitoring. Due to the rich set of features supported by the framework, the games' rehabilitation efficacy can be enhanced primarily from an increase in the patient's motivation when exercising the rehabilitation tasks. Copyright © 2014, IGI Global.

Abstract

Abstract
Bidirectional transformations have potential applications in a vast number of computer science domains. Spreadsheets, on the other hand, are widely used for developing business applications, but their formulas are unidirectional, in the sense that their result can not be edited and propagated back to their input cells. In this paper, we interpret such formulas as a well-known class of bidirectional transformations that go by the name of lenses. Being aimed at users that are not proficient with programming languages, we devote particular attention to the seamless embedding of the proposed bidirectional mechanism with the typical workflow of spreadsheet environments, allowing users to have a fine control and understanding of the behavior of the derived backward transformations.