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Publications

2020

Supplementary Damping Control Design for Large Scale PV Power Plant at Transmission Level Interconnection

Authors
Isbeih, YJ; El Moursi, MS; Lotfi, M; Catalão, JPS; Abdel Rahman, MH;

Publication
IEEE PES Innovative Smart Grid Technologies Europe, ISGT Europe 2020, Delft, The Netherlands, October 26-28, 2020

Abstract
The deployment of large scale photovoltaic (PV) power generation has been witnessed in several countries worldwide with different installed capacities. Accordingly, codes and regulations to ensure secure and economical operation have been revised to address the challenges related with PV integration into electrical networks. This paper presents an H8 mixed sensitivity robust control design for enhancing the overall damping of low frequency oscillations. The presented architecture will implement the output signal of the power oscillator damper (POD) at the control loop of the PV-based solar power plant. The effectiveness of the proposed approach is tested using the New-England, 10machines test system. © 2020 IEEE.

2020

Understanding Service Design and Design Thinking Differences Between Research and Practice: An Empirical Study

Authors
Torres, A; Miranda, C;

Publication
EXPLORING SERVICE SCIENCE (IESS 2020)

Abstract
Service Design (SD) and Design Thinking (DT) evolved in the last decade and have become popular in the research field of service science. However, the application of SD and DT research outcomes into practice is still scarce. To help understanding the differences between research and practice, we conducted 20 semi-structured interviews with professionals and trainees from four organizations that are involved in service innovation projects. The results reveal several similarities and complementarities, (dis)advantages, requests and obstacles, which hinder companies from implementing and using structured SD and DT approaches. The findings present some challenges for both researchers and practitioners on actions they could take to overcome barriers and foster the SD and DT practice within organizations.

2020

AdaptPack Studio: an automated intelligent framework for offline factory programming

Authors
Castro, AL; de Souza, JPC; Rocha, LF; Silva, MF;

Publication
INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION

Abstract
Purpose This paper aims to propose an automated framework for agile development and simulation of robotic palletizing cells. An automatic offline programming tool, for a variety of robot brands, is also introduced. Design/methodology/approach This framework, named AdaptPack Studio, offers a custom-built library to assemble virtual models of palletizing cells, quick connect these models by drag and drop, and perform offline programming of robots and factory equipment in short steps. Findings Simulation and real tests performed showed an improvement in the design, development and operation of robotic palletizing systems. The AdaptPack Studio software was tested and evaluated in a pure simulation case and in a real-world scenario. Results have shown to be concise and accurate, with minor model displacement inaccuracies because of differences between the virtual and real models. Research limitations/implications An intuitive drag and drop layout modeling accelerates the design and setup of robotic palletizing cells and automatic offline generation of robot programs. Furthermore, A* based algorithms generate collision-free trajectories, discretized both in the robot joints space and in the Cartesian space. As a consequence, industrial solutions are available for production in record time, increasing the competitiveness of companies using this tool. Originality/value The AdaptPack Studio framework includes, on a single package, the possibility to program, simulate and generate the robot code for four different brands of robots. Furthermore, the application is tailored for palletizing applications and specifically includes the components (Building Blocks) of a particular company, which allows a very fast development of new solutions. Furthermore, with the inclusion of the Trajectory Planner, it is possible to automatically develop robot trajectories without collisions.

2020

Using Network Features for Credit Scoring in MicroFinance: Extended Abstract

Authors
Paraiso, P; Ruiz, S; Gomes, P; Rodrigues, L; Gama, J;

Publication
2020 IEEE 7TH INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS (DSAA 2020)

Abstract
This paper uses non-traditional data, from a MicroFinance Institution (MFI), in a Credit Scoring loan classification problem and addresses a common problem in emerging markets of the lack of a verifiable customers' credit history. We perform a set of experiments to define a baseline model and prove the relevance of node embedding features, in credit scoring models, using a real world dataset. © 2020 IEEE.

2020

A multi-objective Monte Carlo tree search for forest harvest scheduling

Authors
Neto, T; Constantino, M; Martins, I; Pedroso, JP;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
While the objectives of forest management vary widely and include the protection of resources in protected forests and nature reserves, the primary objective has often been the production of wood products. However, even in this case, forests play a key role in the conservation of living resources. Constraining the areas of clearcuts contributes to this conservation, but if it is too restrictive, a dispersion of small clearcuts across the forest might occur, and forest fragmentation might be a serious ecological problem. Forest fragmentation leads to habitat loss, not only because the forest area is reduced, but also because the core area of the habitats and the connectivity between them decreases. This study presents a Monte Carlo tree search method to solve a bi-objective harvest scheduling problem with constraints on the clearcut area, total habitat area and total core area inside habitats. The two objectives are the maximization of both the net present value and the probability of connectivity index. The method is presented as an approach to assist the decision maker in estimating efficient alternative solutions and the corresponding trade-offs. This approach was tested with instances for forests ranging from some dozens to over a thousand stands and temporal horizons from three to eight periods. In general, multi-objective Monte Carlo tree search was able to find several efficient alternative solutions in a reasonable time, even for medium and large instances.

2020

Preliminary Experiences in Requirements-Based Security Testing

Authors
Miranda, J; Paiva, ACR; da Silva, AR;

Publication
Quality of Information and Communications Technology - 13th International Conference, QUATIC 2020, Faro, Portugal, September 9-11, 2020, Proceedings

Abstract
Software requirements engineers and testers generally define technical documents in natural languages, but this practice can lead to inconsistencies between the documentation and the consequent system implementation. Previous research has shown that writing requirements and tests in a structured way, with controlled natural languages like RSL, can help mitigate these problems. This study goes further, discussing new experiments carried out to validate that RSL (with its complementary tools, called “ITLingo Studio”) can be applied in different systems and technologies, namely the possibility of applying the approach to integrate test automation capabilities in security testing. The preliminary conclusion indicates that, by combining tools such as ITLingo Studio and the Robot Framework, it is possible to integrate requirements and test specifications with test automation, and that would bring benefits in the testing process’ productivity. © Springer Nature Switzerland AG 2020.

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