Abstract
Introduction: Dermoscopy is a non-invasive in vivo imaging technique, used in dermatology in feature identification, among pigmented melanocytic neoplasms, from suspicious skin lesions. Often, in the skin exam is possible to ascertain markers, whose identification and proper characterization is difficult, even when it is used a magnifying lens and a source of light. Dermoscopic images are thus a challenging source of a wide range of digital features, frequently with clinical correlation. Among these markers, one of particular interest to diagnosis in skin evaluation is the reticular pattern. Methods: This paper presents a novel approach (avoiding pre-processing, e.g. segmentation and filtering) for reticular pattern detection in dermoscopic images, using texture spectral analysis. The proposed methodology involves a Curvelet Transform procedure to identify features. Results: Feature extraction is applied to identify a set of discriminant characteristics in the reticular pattern, and it is also employed in the automatic classification task. The results obtained are encouraging, presenting Sensitivity and Specificity of 82.35% and 76.79%, respectively. Conclusions: These results highlight the use of automatic classification, in the context of artificial intelligence, within a computer-aided diagnosis strategy, as a strong tool to help the human decision making task in clinical practice. Moreover, the results were obtained using images from three different sources, without previous lesion segmentation, achieving to a rapid, robust and low complexity methodology. These properties boost the presented approach to be easily used in clinical practice as an aid to the diagnostic process.

Abstract
In this paper we present a new concept of robot-dependent reachability map (RDReachMap) for mobile platforms. In heterogeneous multi-robot systems, the reachability limit of robots motion and actuation must be considered when assigning tasks to them. We created an algorithm that generates those reachability maps, separating regions that can be covered by a robot from the unreachable ones, using morphological operations. Our method is dependent on the robot position, and is parameterized with the robot's size and actuation radius. For this purpose we introduce a new technique, the partial morphological closing operation. The algorithm was tested both in simulated and real environment maps. We also present a common problem of multi robot routing, which we solve with a planner that uses our reachability maps in order to generate valid plans. We contribute a heuristic that generates paths for two robots using the reachability concept.

Abstract
The growing dependence of our society on increasingly complex software systems makes software testing ever more important and challenging. In many domains, such as healthcare and transportation, several independent systems, forming a heterogeneous and distributed system of systems, are involved in the provisioning of end-to-end services to users. However, existing testing techniques, namely in the model-based testing field, provide little support for properly testing such systems. To bridge the gaps identified in the state of the art we intend to develop a research work where the main goal is to significantly reduce the cost of testing distributed and heterogeneous systems, from the standpoint of time, resources and expertise required, as compared to existing approaches. For that, we propose a preliminary approach and a toolset architecture for automating the testing of end-to-end services in distributed and heterogeneous systems. The tester interacts with a visual modeling frontend to describe key behavioral scenarios, invoke test generation and execution, and visualize test results and coverage information back in the model. The visual modeling notation is converted to a formal notation amenable for runtime interpretation in the backend. A distributed test monitoring and control infrastructure is responsible for interacting with the components of the system under test, as test driver, monitor and stub. At the core of the toolset, a test execution engine coordinates test execution and checks the conformance of the observed execution trace with the expectations derived from the visual model. A real world example from the Ambient Assisted Living domain is presented to illustrate the approach. As future work we intend to develop distributed and incremental algorithms for online testing of distributed and heterogeneous systems based on Extended Petri Nets at runtime and validate them in real world case studies.

Abstract
There is currently a significant interest in consumer electronics in applications and devices that monitor and improve the user's well-being. This is one of the key aspects in the development of ambient intelligence systems. Nonetheless, existing approaches are generally based on physiological sensors, which are intrusive and cannot be realistically used, especially in ambient intelligence in which the transparency, pervasiveness and sensitivity are paramount. We put forward a new approach to the problem in which user behavioral cues are used as an input to assess inner state. This innovative approach has been validated by research in the last years and has characteristics that may enable the development of true unobtrusive, pervasive and sensitive ambient intelligent systems.

Abstract
In the web environment, most of the queries issued by users are implicit by nature. Inferring the different temporal intents of this type of query enhances the overall temporal part of the web search results. Previous works tackling this problem usually focused on news queries, where the retrieval of the most recent results related to the query are usually sufficient to meet the user's information needs. However, few works have studied the importance of time in queries such as "Philip Seymour Hoffman" where the results may require no recency at all. In this work, we focus on this type of queries named "time-sensitive queries" where the results are preferably from a diversified time span, not necessarily the most recent one. Unlike related work, we follow a content-based approach to identify the most important time periods of the query and integrate time into a re-ranking model to boost the retrieval of documents whose contents match the query time period. For that purpose, we define a linear combination of topical and temporal scores, which reflects the relevance of any web document both in the topical and temporal dimensions, thus contributing to improve the effectiveness of the ranked results across different types of queries. Our approach relies on a novel temporal similarity measure that is capable of determining the most important dates for a query, while filtering out the non-relevant ones. Through extensive experimental evaluation over web corpora, we show that our model offers promising results compared to baseline approaches. As a result of our investigation, we publicly provide a set of web services and a web search interface so that the system can be graphically explored by the research community.

Abstract
Cyber-physical systems constitutes a framework to develop intelligent, distributed, resilient, collaborative and cooperative systems, promoting the fusion of computational entities and physical devices. Agent technology plays a crucial role to develop this kind of systems by offering a decentralized, distributed, modular, robust and reconfigurable control structure. This paper describes the implementation of a summer school aiming to enhance the participants' knowledge in the field of multi-agent systems applied to industrial environments, being able to gain the necessary theoretical and practical skills to develop real industrial agent based applications. This is accomplished in an international framework where individual knowledge and experiences are shared in a complementary level.