Abstract
As technology evolves, frauds, in all their different forms, become increasingly more complex, as mega-processes such as Luanda Leaks or Panama Papers have recently shown. Fraud detection mechanisms must thus also resort to recent technological developments to ensure that even new forms of complex fraud are detected in time. In this paper we present a system to facilitate fraud detection in Public Procurement in Portugal. It relies on three main components. Data on public procurement and involved entities is acquired from public sources and integrated into a graph-oriented database. A rules-engine enriches these data with information additional information, using legal rules or custom rules defined by the users. Finally, a graph-oriented User Interface is used to support decision-making, allowing users to quickly and efficiently explore and filter information, in a natural and geo-referenced way. The main goal of this system is to increase transparency by facilitating access to relevant information, and in this way contribute to the fairness of the whole public procurement procedure. © 2020, Springer Nature Switzerland AG.

Abstract
The learning of programming is traditionally challenging for students. However, this is also one of the most fundamental skills for any computer scientist, and is becoming an important skill in other areas of knowledge. In this paper we analyze the use of game-elements in a challenging long-term programming task, with students of the 3rd year of a Informatics Engineering degree. We conducted a quantitative study using the AMS scale to assess students' motivation. Results show that with the use of game-elements, students are both intrinsically and extrinsically motivated, and that they consider learning/working fun, which contributes positively to their academic performance. 2012 ACM Subject Classification Human-centered computing!Collaborative and social computing theory, concepts and paradigms.

Abstract

Abstract
Sustainability and eco-efficiency have been researched in multiple scientific papers since the last years. However the literature is not so abundant when applying those concepts to industrial assembly processes. This paper presents an innovate methodology to optimize aerospace assembly processes. Authors propose the introduction of a new element, the eco-efficiency, along with the traditional criteria, cost and time, currently used for optimization. Using a large Aero-Structure as an industrial case of study, the methodology analyzes the eco-efficiency of an assembly process in connection with a Life Cycle Assessment (LCA) to compute the environmental impact. Results are shown in a dashboard along with the relevant Key Process Indicator (KPI) to help the engineers to select the best assembly process. © 2020, IFIP International Federation for Information Processing.

Abstract
Additive Manufacturing (AM) is one of the most trending production technologies, with a growing number of companies looking forward to implementing it in their processes. Producing through AM not only means that there are no supplier lead times needed to account for, but also enables production closer to the end customer, reducing then the delivery time. This is especially true for companies with a wide range of low and variable demand products. This paper proposes a mixed integer linear programming (MILP) model for the optimal design of supply chains facing the introduction of AM processes. In the addressed problem, the 3D printers allocation to distribution centers (DC), that will make or customize parts, and the Suppliers-DC-Customers connections for each product need to be defined. The model aims at minimizing the supply chain costs, exploring the trade-offs between safety stock and stockout costs, and between buying and 3D printing a part. The main relevant characteristics of this model are the introduction of stock service levels as decision variables and the use of a linearization of the cumulative distribution function to account for demand uncertainty. A real-world problem from a maintenance provider is solved, showing the applicability of the model. © 2019, IEOM Society International.

Abstract
In recent years, cognitive robots have started to find their way into manufacturing halls. However, the full potential of these robots can only be exploited through (a) an integration of the robots with the Manufacturing Execution System (MES), (b) a new and simpler way of programming based on robot skills, automated task planning, and knowledge modeling, and (c) enabling the robots to function in a shared human/robot workspace with the ability to handle unexpected situations. The STAMINA project has built a robotic system that meets these objectives for an automotive kitting application, which has also been tested, validated, and demonstrated in a relevant environment (TRL6). This paper describes the STAMINA robot system and the evaluation of this system on a series of realistic kitting tasks. The structure of the system, evaluation methodology, and experimental results, are presented along with the insights and experiences gained from this work.