Abstract
This study gives suggestions on how to decrease academic cheating. This exploratory study discusses how engaging students, with the case study approach, has led to the submission of more honest course work. What needs to change is the challenge – requiring too much is worse than not requiring anything at all, as the former is an incentive to academic cheating. Students need reachable goals and not to be over-swamped with course work. In the UK this may seem obvious but not so in other countries, where a number of students are known for copying and for not submitting original work to their lecturers (Teixeira, 2011). How might one attempt to change this trend of trying to get around the education system? This paper is about how to engage students – be it in the classroom, be it when they are at home, doing their course work. If it may be true that success is all about how much work you put in (Oliveira, 1993; Mansfield and Oliveira, 1994, 1995), then success in academia is about how you motivate students to want to excel based on their own merit and hard work (Au-Yong-Oliveira and Almeida, 2015). Rather than measuring a lecturer’s success on his or her pass rates of students, or by judging him or her on satisfaction scores given by students, lecturers should recognize that what is required is that they have a lasting effect on their students – in essence, changing their lives. Why are starting salaries so low in Portugal? Why is it so hard for students who have just graduated to find a job in Portugal? Why is the immigration rate so high amongst Portugal’s youths? A lot has to do with the education system – which is, albeit, at some institutions, already very practical, in the management studies domain. What we discuss herein is how to elicit honest contributions and how to gain genuine interest from higher education students – both at the undergraduate as well as postgraduate levels. Certain academic environments need change. This paper is about how to bring about that change and what lecturers can do, in particular with regards to research methodology, to revolutionize academia and perhaps even youth employment rates in the country. The account is by lecturers with teaching experience in a dozen higher education institutions. Having worked with Erasmus students the authors are well aware that plagiarism is also a problem in other countries, besides Portugal – notably, in Spain, Greece, and new democracies in Eastern Europe.

Abstract
The realization of tabletop optical analogue experiments of superfluidity relies on the engineering of suitable optical media, with tailored optical properties. This work shows how quantum atomic optical systems can be used to develop highly tunable optical media, with localized control of both linear and nonlinear susceptibility. Introducing the hydrodynamic description of light, the superfluidity of light in these atomic media is investigated through GPU-enhanced numerical simulations, with the numeric observation of the superfluidic signature of suppressed scattering through a defect.

Abstract
This paper addresses the problem of collision avoidance along specified paths in multiple mobile robot systems. These collisions can be represented by points of intersection or coincident segments between paths. The proposal of the work is to model these segments where the collision is possible through fictitious points. In addition, the advantages of the nonlinear versus mixed integer linear formulation, widely used in the literature, are verified. Comparisons were made and it’s proved the superiority of the proposed method with respect to complexity, computational time and inclusion of nonlinear constraints. Moreover, the simulations performed using this technique indicate that the method is promissory for applications in real systems.

Abstract
This paper describes the application of a Brain Emotional Learning (BEL) controller to improve the response of a SDOF structural system under an earthquake excitation using a magnetorheological (MR) damper. The main goal is to study the performance of a BEL based semi-active control system to generate the control signal for a MR damper. The proposed approach consists of a two controllers: a primary controller based on a BEL algorithm that determines the desired damping force from the system response and a secondary controller that modifies the input current to the MR damper to generate a reference damping force. A parametric model of the damper is used to predict the damping force based on the piston motion and also the current input. A Simulink model of the structural system is developed to analyze the effectiveness of the semi-active controller. Finally, the numerical results are presented and discussed. © Springer International Publishing Switzerland 2017.

Abstract
Machine Learning (ML) has been successfully applied to a wide range of domains and applications. One of the techniques behind most of these successful applications is Ensemble Learning (EL), the field of ML that gave birth to methods such as Random Forests or Boosting. The complexity of applying these techniques together with the market scarcity on ML experts, has created the need for systems that enable a fast and easy drop-in replacement for ML libraries. Automated machine learning (autoML) is the field of ML that attempts to answers these needs. We propose autoBagging, an autoML system that automatically ranks 63 bagging workflows by exploiting past performance and metalearning. Results on 140 classification datasets from the OpenML platform show that autoBagging can yield better performance than the Average Rank method and achieve results that are not statistically different from an ideal model that systematically selects the best workflow for each dataset. For the purpose of reproducibility and generalizability, autoBagging is publicly available as an R package on CRAN.

Abstract
Tactical production-distribution "planning models have attracted a great deal of attention in the past decades. In these models, production and distribution decisions are considered simultaneously such that the combined plans are more advantageous than the plans resolved in a hierarchical planning process. We consider a two-stage production process, where in the first stage raw materials are transformed into continuous resources that feed the discrete production of end products in the second stage. Moreover, the setup times and costs of resources depend on the sequence in which they are processed in the first stage. The minimum scheduling unit is the product family which consists of products sharing common resources and manufacturing processes. Based on different mathematical modelling approaches to the production in the first stage, we develop a sequence-oriented formulation and a product-oriented formulation, and propose decomposition-based heuristics to solve this problem efficiently. By considering these dependencies arising in practical production processes, our model can be applied to various industrial cases, such as the beverage industry or the steel industry. Computation tests on instances from an industrial application are provided at the end of the paper.