Abstract
In obstructive sleep apnea, respiratory effort is maintained but ventilation decreases/disappears due to upper-airway partial/total occlusion. This condition affects about 4% of men and 2% of women worldwide. This study aimed to define an auxiliary diagnostic method that can support the decision to perform polysomnography, based on risk and diagnostic factors. Our sample performed polysomnography between January and May 2015. Two Bayesian classifiers were used to build the models: Naïve Bayes and Tree Augmented Naïve Bayes, using 38 variables identified by literature review or just a selection of 6. Area under the ROC curve, sensitivity, specificity and predictive values were evaluated using leave-one-out and cross-validation techniques. From a total of 241 patients, only 194 fulfilled the inclusion criteria, 123 (63%) were male, with a mean age of 58 years, 66 (34%) patients had a normal result and 128 (66%) a diagnosis of obstructive sleep apnea. The cross-validated AUCs for each model were: NB38: 69.2%; TAN38: 69.0%; NB6: 74.6% and TAN6: 63.6%. Regarding risk matrix, female gender presented a starting rate of 8%, comparing to 20% in male gender, almost 3 times higher. The high (34%) proportion of normal results confirms the need for a pre-evaluation prior to polysomnography, making the search for a validated model to screen patients with suspicion of obstructive sleep apnea essential, especially at primary care level.

Abstract
The overall aim of the ROSM project is the implementation of an innovative solution based on heterogeneous autonomous vehicles to tackle maritime pollution (in particular, oil spills). These solutions will be based on native microbial consortia with bioremediation capacity, and the adaptation of air and surface autonomous vehicles for in-situ release of autochthonous microorganisms (bioaugmentation) and nutrients (biostimulation). By doing so, these systems can be used as the first line of the responder to pollution incidents from several origins that may occur inside ports, around industrial and extraction facilities, or during transport activities, in a fast, efficient and low-cost way. The paper will address the development of a team of autonomous vehicles able to carry, as payload, native organisms to naturally degrade oil spills (avoiding the introduction of additional chemical or biological additives), the development of a multi-robot system able to provide a first line responses to oil spill incidents under unfavourable and harsh conditions with low human intervention, and then a decentralized cooperative planning with the ability to coordinate an efficient oil spill combat. Field tests have been performed in Leixoes Harbour in Porto and Medas, Portugal, with a simulated oil spill and validated the decentralized coordinated task between the autonomous surface vehicle (ASV) ROAZ and the unmanned aerial vehicle (UAV).

Abstract
The tourism sector has become one of the most important engines of economic growth for many countries. With the evolution of Information and Communication Technologies, new opportunities have arisen for a reengineering in the way the various tourism and hospitality industries interact with tourists. Equally, new possibilities open to the entities that vision to promote the patrimony and endogenous products of their regions. Information and Communication Technologies are today one of the most critical areas for the success of tourism and how tourist destinations can be promoted. Tourists, increasingly a digital generation, expect that the access to information and services be done in an innovative, immersive and contextualized way, through the use of technologies that are embedded in their daily lives. This article discusses the touristic routes creation process and the role of Information and Communication Technologies in the creation and support of touristic routes. Also, a technological model is presented in its conceptual perspective, as well the functional modelling of its main components and features.

Abstract
Security is now becoming a well-established challenge for integrated circuits (ICs). Various types of IC attacks have been reported, including reverse engineering IPs, dumping on-chip data, and controlling/modifying IC operation. IEEE 1149.1, commonly known as Joint Test Action Group (JTAG), is a standard for providing test access to an IC. JTAG is primarily used for IC manufacturing test, but also for in-field debugging and failure analysis since it gives access to internal subsystems of the IC. Because the JTAG needs to be left intact and operational after fabrication, it inevitably provides a "backdoor" that can be exploited outside its intended use. This paper proposes machine learning-based approaches to detect illegitimate use of the JTAG. Specifically, JTAG operation is characterized using various features that are then classified as either legitimate or attack. Experiments using the OpenSPARC T2 platform demonstrate that the proposed approaches can classify legitimate JTAG operation and known attacks with significantly high accuracy. Experiments also demonstrate that unknown and disguised attacks can be detected with high accuracy as well (99% and 94%, respectively).

Abstract
Because of terminology mismatches, health consumers frequently face difficulties while searching the Web for health information. Difficulties arise in query formulation but also in understanding the retrieved documents. In this work we analyze how documents' readability affects users' comprehension and how both affect the retrieval performance, measured in different ways. In addition, we analyze how performance measures relate with each other. For this purpose we have conducted a laboratory user study with 40 participants. We found that readability is essential for a document to be at least partially relevant and that it becomes even more important if the document has medico-scientific terminology. Moreover, the relevance of a document to a specific user highly depends on its comprehension. In lay queries we found the medical accuracy of users' answers is related to the session's relevance assessments. This shows that users can, at least in part, relate their relevance assessments with the medical accuracy of the documents. On the other hand, this relationship does not exist with medico-scientific queries.

Abstract
This paper presents an overview on how the European Project Semester capstone programme offered by the Instituto Superior de Engenharia do Porto (EPS@ISEP) fosters learning by challenging engineering, business and product development undergraduates to address sustainability issues afflicting cities and communities nowadays. This will be done by analysing the reports and the learning journey of three multicultural and multidisciplinary EPS@ISEP teams during the design, development and test of a smart billboard, a self-oriented solar mirror and a level monitoring system for waste oil bins. These three projects were conducted within EPS@ISEP, a project-based learning framework dedicated to the development of key engineering skills, namely multidisciplinary teamwork, intercultural communication, ethical and sustainability-oriented problem-solving. The involved students contributed, not only, to make cities more inclusive, safe, resilient and sustainable, one of UNESCO's sustainable development goals, but learnt and practiced together sustainability-driven design, while searching for an innovative solution for a smart city problem. This conclusion is supported by the analysis of the content the three project reports.