Abstract
In movie/TV collaborative recommendation approaches, ratings users gave to already visited content are often used as the only input to build profiles. However, users might have rated equally the same movie but due to different reasons: either because of its genre, the crew or the director. In such cases, this rating is insufficient to represent in detail users' preferences and it is wrong to conclude that they share similar tastes. The work presented in this paper tries to solve this ambiguity by exploiting hidden semantics in metadata elements. The influence of each of the standard description elements (actors, directors and genre) in representing user's preferences is analyzed. Simulations were conducted using Movielens and Netflix datasets and different evaluation metrics were considered. The results demonstrate that the implemented approach yields significant advantages both in terms of improving performance, as well as in dealing with common limitations of standard collaborative algorithm.

Abstract
Nowadays using E-learning platforms such as Intelligent Tutoring Systems (ITS) that support users to learn subjects are quite common. Despite the availability and the advantages of these systems, they ignore the learners' time limitation for learning a subject. In this paper we propose RUTICO, that recommends successful learning paths with respect to a learner's knowledge background and under a time constraint. RUTICO, which is an example of Long Term goal Recommender Systems (LTRS), a.er locating a learner in the course graph, it utilizes a Depth-first search (DFS) algorithm to find all possible paths for a learner given a time restriction. RUTICO also estimates learning time and score for the paths and finally, it recommends a path with the maximum score that satisfies the learner time restriction. In order to evaluate the ability of RUTICO in estimating time and score for paths, we used the Mean Absolute Error and Error. Our results show that we are able to generate a learning path that maximizes a learner's score under a time restriction.

Abstract
Em cada pessoa existe um potencial empreendedor sendo a educação para o empreendedorismo o meio mais eficaz para o dinamizar e promover (Dolabela, 2008). Contudo, como abordar um tema tão complexo com crianças? Objetivo: Identificar a existência ou não de características empreendedoras em contexto de narração de história em crianças. Participantes: Uma turma do 1º ano com 18 alunos e uma de 3º ano com 19 alunos entre os 6 e os 9 anos (7,2±1,1) de uma escola de Braga. Instrumentos/Procedimentos: Construíram-se categorias e subcategorias suportadas pela revisão da literatura que determinaram as características empreendedoras a avaliar. Elaborou-se uma história construída de raiz, tendo por base o tema piratas e a procura de tesouros. Trata-se de uma história dinâmica, em que, cada uma das suas etapas termina com um desafio ou questão para os alunos. Assim, estes podem assumir-se como personagens, dar sugestões argumentadas sobre o caminho a seguir na história e ainda fazer opções entre várias possíveis. A história foi aplicada, em cada um dos anos de escolaridade, em grupos focais, de seis crianças. Discussão dos resultados: A observação das diferentes subcategorias permitiram-nos verificar comportamentos positivos (CP), inversos (CI) e não observados (CNO). Constatamos que em cinco das oito categorias a maioria dos alunos as revelou de forma positiva com destaque para a “Autoconfiança” e “Relações interpessoais” e ainda que aquelas em que se verificou maior percentagem de alunos que manifestaram CI foram a “Autoconfiança”, “Relações interpessoais” destacando-se a “Persistência/Resistência ao Fracasso. As categorias em que mais se verificaram CNO foram a “Liderança / Tomada de decisão” e “Organização e Planeamento”. São necessárias mais investigações de forma a reunir um número considerável de contribuições para a validação de um instrumento que se adapte à linguagem da criança e que, de uma forma lúdica e motivadora, permita identificar características empreendedoras.

Abstract
In the current world, performance is one of the most important issues concerning work and competition. Performance is strongly connected with learning and when it comes to acquiring new knowledge, attention is one the most important mechanisms as the level of the learner's attention affects learning results. When students are doing learning activities using new technologies, it is extremely important that the teacher has some feedback from the students' work in order to detect potential learning problems at an early stage. The goal of this research is to propose a system that measures the level of attentiveness in real scenarios, and detects patterns of behavior associated to different attention levels among different students. This system measures attention and uses this information for training a decision support system that shows the level of attention of a group of students in real time.

Abstract
The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable technology to deploy wide-scale Wireless Sensor Networks (WSNs). These networks are usually designed to support convergecast traffic, where all communication paths go through the PAN (Personal Area Network) coordinator. Nevertheless, peer-to-peer communication relationships may be also required for different types of WSN applications. That is the typical case of sensor and actuator networks, where local control loops must be closed using a reduced number of communication hops. The use of communication schemes optimised just for the support of convergecast traffic may result in higher network congestion and in a potentially higher number of communication hops. Within this context, this paper proposes an Alternative-Route Definition (ARounD) communication scheme for WSNs. The underlying idea of ARounD is to setup alternative communication paths between specific source and destination nodes, avoiding congested cluster-tree paths. These alternative paths consider shorter inter-cluster paths, using a set of intermediate nodes to relay messages during their inactive periods in the cluster-tree network. Simulation results show that the ARounD communication scheme can significantly decrease the end-to-end communication delay, when compared to the use of standard cluster-tree communication schemes. Moreover, the ARounD communication scheme is able to reduce the network congestion around the PAN coordinator, enabling the reduction of the number of message drops due to queue overflows in the cluster-tree network.

Abstract
Typical vehicle suspension systems are based on passive energy dissipation devices. This type of systems have proven to be a reliable and economic approach, however they are not capable to modify its behavior in accordance with the road conditions. On the other hand, active systems allow a continuous control of the suspension response although requiring sensors, actuators and controllers which represents a more complex and expensive system, usually demanding high power requirements. A middle-term vibration control approach is to use the so-called semi-active systems with the adaptability of active systems and lower energy consumption. This paper aims to evaluate the comfort ridding of a full suspension bicycle equipped with semi-active open loop controlled suspension system using a magneto-rheological (MR) damper. The assessment was carried out based on the analysis of real data, extracted from the instrumented bicycle prototype. The experimental tests were made in a smooth indoor pavement and a cobblestone road. Finally, the results obtained with the proposed semi-active suspension control system are presented and discussed.