Abstract
We present a study in the area of sentiment analysis of clients' commentaries transcribed by assistants of a help-desk service of one Portuguese telecommunications company. We have adopted a lexicon-based approach to determine the polarity of the sentiment of each commentary, based on the so called opinion words. This task was by no means easy, as not many tools are available for the Portuguese language. The initial results with the off-the-shelf solutions were rather poor. This has motivated us to carry out a number of enhancements, including, for instance, enriching the given lexicon with domain specific terms, formulating specific rules for negation and amplifiers. Automatic pruning of some of the lexicon terms has led to a significant improvement in performance. As our final system achieved a very good performance, our work should be of interest to others working on domain specific solutions for languages where ready-made solutions are not available.

Abstract
In the design of computer-aided diagnosis systems for lung cancer diagnosis, an appropriate and accurate segmentation of the pulmonary nodules in computerized tomography (CT) is one of the most relevant and difficult tasks. An accurate segmentation is crucial for the posterior measurement of nodule characteristics and for lung cancer diagnosis. This paper proposes different approaches that use Hessian-based strategies for lung nodule segmentation in chest CT scans. We propose a multiscale segmentation process that uses the central medialness adaptive principle, a Hessian-based strategy that was originally formulated for tubular extraction but it also provides good segmentation results in blob-like structures as is the case of lung nodules. We compared this proposal with a well established Hessian-based strategy that calculates the Shape Index (SI) and Curvedness (CV). We adapted the SI and CV approach for multiscale nodule segmentation. Moreover, we propose the combination of both strategies by combining the results, in order to take benefit of the advantages of both strategies. Different cases with pulmonary nodules from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) database were taken and used to analyze and validate the approaches. The chest CT images present a large variability in nodule characteristics and image conditions. Our proposals provide an accurate lung nodule segmentation, similar to radiologists performance. Our Hessian-based approaches were validated with 569 solid and mostly solid nodules demonstrating that these novel strategies have good results when compared with the radiologists segmentations, providing accurate pulmonary nodule volumes for posterior characterization and appropriate diagnosis.

Abstract
Gastroenterology imaging is a diagnostic procedure that incorporates various computer vision challenges for the design of assisted diagnostic systems. The most typical challenge is the design of more adequate visual descriptors that can assist the classification algorithms in getting good diagnostic results. Literature shows that most of the texture descriptors for feature extraction from gastric lesions are based on Gabor filters or local binary patterns (LBP). Although good results are obtained, these techniques have their shortcomings. In this paper, we aim to explore the use of fusion of Gabor filters and LBPs for characterizing gastric lesions. The images are first subjected to Gabor filtering using isotropic Gabor filters, followed by extracting LBPs from the filtered images. We validate the performance of the descriptor on a novel gastroenterology dataset: the Post-MAPS dataset. Our results show that the proposed feature set outperforms the other methods that have been considered in this paper.

Abstract
Stroke episodes are a major health issue worldwide for which most patients require an initial period of special rehabilitation and functional treatment, involving medical doctors and specialized therapists, followed by ambulatory physiotherapy exercise. In this second period most do not fulfil the prescribed recovery plan, resulting in setbacks in their recovery. This paper reports on the design of a methodology to develop a system to support the ambulatory rehabilitation therapy, providing constant feedback to the clinicians, by means of an information system platform, and maintaining the patient motivation by using an exergames approach to design and deliver the therapy exercises to the patient.

Abstract
The European Project Semester (EPS) is a one-semester capstone project/internship programme offered to engineering, product design and business undergraduates by 18 European engineering schools. EPS aims to prepare future engineers to think and act globally, by adopting project-based learning and teamwork methodologies, fostering the development of complementary skills and addressing sustainability and multiculturalism. Since 2011, the EPS@ISEP programme offers a set of multidisciplinary projects to multicultural teams of students, so that each team element can bring to the project its previous knowledge and background experience. In the spring of 2013, a team choose to develop a pet tracker to provide pet owners with information regarding the whereabouts of their pets and, above all, to reduce the number of pets lost. After analysing related products, the team decided to add extra features for product differentiation. Combining a triple-axis accelerometer, a low cost GPS receiver and the GSM/GPRS communication technology, the team designed a system providing pet location, tracking, map display and activity monitoring services. This paper describes the development process of the Pet Tracker system, comprising a wearable device for pets and a website for pet owners.

Abstract
The actual flexibility of the electricity sector, with a distributed nature and new players, such as the smart grid operator and several types of aggregators, brings new business models and introduces new challenges from the power systems technical operation point of view. In this context, the Network Operator Agent of the Multi-Agent Simulator of Competitive Electricity Markets ( MASCEM) plays a crucial role, not only in the scope of the technical validation of the economic transactions established by the market, but also has an agent that can be supporting the grid operation under the scope of a smart grid. A set of new features has been added to the Network Operator making it a "new agent", bringing a more effective decision support, from the grid technical operation point of view, and achieving its usefulness beyond MASCEM. In this paper the new features are described. A case study is also included to better illustrate the approach and to highlight its usefulness under the scope of a smart grid scenario.