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Publications

Publications by CRAS

2021

New metrology for radon at the environmental level

Authors
Röttger, A; Röttger, S; Grossi, C; Vargas, A; Curcoll, R; Otáhal, P; Hernández-Ceballos, MÁ; Cinelli, G; Chambers, S; Barbosa, SA; Ioan, M; Radulescu, I; Kikaj, D; Chung, E; Arnold, T; Yver Kwok, C; Fuente, M; Mertes, F; Morosh, V;

Publication
Measurement Science and Technology

Abstract

2021

Autonomous High-Resolution Image Acquisition System for Plankton

Authors
Resende, J; Barbosa, P; Almeida, J; Martins, A;

Publication
2021 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Abstract

2021

The MopBot Cleaning Robot – An EPS@ISEP 2020 Project

Authors
Tuluc, C; Verberne, F; Lasota, S; de Almeida, T; Malheiro, B; Justo, J; Ribeiro, C; Silva, MF; Ferreira, P; Guedes, P;

Publication
Educating Engineers for Future Industrial Revolutions - Advances in Intelligent Systems and Computing

Abstract

2021

Towards Top-Up Prediction on Telco Operators

Authors
Alves, PM; Filipe, RA; Malheiro, B;

Publication
Progress in Artificial Intelligence - 20th EPIA Conference on Artificial Intelligence, EPIA 2021, Virtual Event, September 7-9, 2021, Proceedings

Abstract
In spite of their growing maturity, telecommunication operators lack complete client characterisation, essential to improve quality of service. Additionally, studies show that the cost to retain a client is lower than the cost associated to acquire new ones. Hence, understanding and predicting future client actions is a trend on the rise, crucial to improve the relationship between operator and client. In this paper, we focus in pay-as-you-go clients with uneven top-ups. We aim to determine to what extent we are able to predict the individual frequency and average value of monthly top-ups. To answer this question, we resort to a Portuguese mobile network operator data set with around 200 000 clients, and nine-month of client top-up events, to build client profiles. The proposed method adopts sliding window multiple linear regression and accuracy metrics to determine the best set of features and window size for the prediction of the individual top-up monthly frequency and monthly value. Results are very promising, showing that it is possible to estimate the upcoming individual target values with high accuracy. © 2021, Springer Nature Switzerland AG.

2021

Design, Modeling, and Simulation of a Wing Sail Land Yacht

Authors
Tinoco, V; Malheiro, B; Silva, MF;

Publication
Applied Sciences

Abstract
Autonomous land yachts can play a major role in the context of environmental monitoring, namely, in open, flat, windy regions, such as iced planes or sandy shorelines. This work addresses the design, modeling, and simulation of a land yacht probe equipped with a rigid free-rotating wing sail and tail flap. The wing was designed with a symmetrical airfoil and dimensions to provide the necessary thrust to displace the vehicle. Specifically, it proposes a novel design and simulation method for free rotating wing sail autonomous land yachts. The simulation relies on the Gazebo simulator together with the Robotic Operating System (ROS) middleware. It uses a modified Gazebo aerodynamics plugin to generate the lift and drag forces and the yawing moment, two newly created plugins, one to act as a wind sensor and the other to set the wing flap angular position, and the 3D model of the land yacht created with Fusion 360. The wing sail aligns automatically to the wind direction and can be set to any given angle of attack, stabilizing after a few seconds. Finally, the obtained polar diagram characterizes the expected sailing performance of the land yacht. The described method can be adopted to evaluate different wing sail configurations, as well as control techniques, for autonomous land yachts.

2021

Smart Bicycle Probe – An EPS@ISEP 2020 Project

Authors
Boularas, M; Szmytke, Z; Smith, L; Isik, K; Ruusunen, J; Malheiro, B; Justo, J; Ribeiro, C; Silva, MF; Ferreira, P; Guedes, P;

Publication
Educating Engineers for Future Industrial Revolutions - Advances in Intelligent Systems and Computing

Abstract

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