Abstract
Este projeto de investigação, em fase de desenvolvimento, visa conceber e implementar a Gamificação de uma rede social académica baseada na plataforma Ellg customizada. A revisão da literatura sobre gamificação em educação evidencia factores de impacto na aprendizagem e envolvimento dos indivíduos. potenciando o desenvolvimento de comunidades e de aprendizagem social. A comunicação pretende descrever o desenvolvimento e a implementação de um projeto de gamificação no ensino superior, as suas fases e desenvolvimento de um protótipo e as expetativas de implementação na plataforma. Fundamentando-se na investigação sobre Comunidades e o modelo COI, na Aprendizagem Social e na Gamificação e o seu uso em Educação, apresenta-se o contexto, as fases do projeto e uma breve apresentação dos resultados já obtidos.

Abstract
It is known that code readability has an impact on software quality. This paper introduces a preliminary list of 33 good practices for code readability that could be taught in object oriented programming courses of informatics programs. In this set are included practices with both positive and negative impact, the latter mainly from bad smells. A survey was made with OOP teachers in order to assess the significance of teaching a set of good practices. The results showed that teachers consider it important to teach the defined set. Such result was statistically significant. Still, the same level of significance was not awarded to all practices. Some additional results are presented.

Abstract
In this paper, an overview is given of the project data instances available in the literature to carry out academic research in the field of integrated project management and control. This research field aims at integrating static planning methods and risk analyses with dynamic project control methodologies using the state-of-the-art knowledge from literature and the best practices from the professional project management discipline. Various subtopics of this challenging discipline have been investigated from different angles, each time using project data available in literature, obtained from project data generators or based on a sample of empirical case studies. This paper gives an overall overview of the wide variety of project data that are available and are used in various research publications. It will be shown how the combination of artificial data and empirical data leads to improved knowledge on and deeper insights into the structure and characteristics of projects useful for academic research and professional use. While the artificial data can be best used to test novel ideas under a strict design in a controlled academic environment, empirical data can serve as the necessary validation step to translate the academic research results into practical ideas, aiming at narrowing the bridge between the theoretical knowledge and practical relevance. A summary of the available project data discussed in this paper can be downloaded from http://www.projectmanagement.ugent.be/research/data.

Abstract
This paper presents a new solution approach to solve the resource-constrained project scheduling problem in the presence of three types of logical constraints. Apart from the traditional AND constraints with minimal time-lags, these precedences are extended to OR constraints and bidirectional (BI) relations. These logical constraints extend the set of relations between pairs of activities and make the RCPSP definition somewhat different from the traditional RCPSP research topics in literature. It is known that the RCPSP with AND constraints, and hence its extension to OR and BI constraints, is NP-hard. The new algorithm consists of a set of network transformation rules that removes the OR and BI logical constraints to transform them into AND constraints and hereby extends the set of activities to maintain the original logic. A satisfiability (SAT) solver is used to guarantee the original precedence logic and is embedded in a metaheuristic search to resource feasible schedules that respect both the limited renewable resource availability as well as the precedence logic. Computational results on two well-known datasets from literature show that the algorithm can compete with the multi-mode algorithms from literature when no logical constraints are taken into account. When the logical constraints are taken into account, the algorithm can report major reductions in the project makespan for most of the instances within a reasonable time.

Abstract
In Project TEMPUS “Enhancement of Russian Creative Education: new Master Programme in Digital Arts in line with EU standards” (2014-2016) the Russian students had the opportunity to study in EU Universities for one semester. The Universidade Aberta, in Portugal, didn’t have a master degree in Digital Arts so a pilot programme had to be created: a new postgraduation in Digital Art Practice. This new curriculum, using blearning (based on online and face to face activities) with transdisciplinary methods, aims a practice oriented training on digital art. It started with a deep understanding of Lisbon, the relationship between people, cultural and artistic spaces and their environments. This knowledge inspired the students to produce and to create an artistic artefact presented in exhibition to an audience. With this postgraduation new possibilities started for reflection about global challenges for education in the millennium.

Abstract
Software Defined Networks (SDNs) provides a separation between the control plane and the forwarding plane of networks. The software implementation of the control plane and the built in data collection mechanisms of the OpenFlow protocol promise to be excellent tools to implement Machine Learning (ML) network control applications. A first step in that direction is to understand the type of data that can be collected in SDNs and how information can be learned from that data. In this work we describe a simple architecture deployed in an enterprise network that gathers traffic data using the OpenFlow protocol. We present the data-sets that can be obtained and show how several ML techniques can be applied to it for traffic classification. The results indicate that high accuracy classification can be obtained with the data-sets using supervised learning.