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J.M.G. Sá da Costa

Researcher at Technical University of Lisbon

Publications -  101
Citations -  4552

J.M.G. Sá da Costa is an academic researcher from Technical University of Lisbon. The author has contributed to research in topics: Fuzzy logic & Fault detection and isolation. The author has an hindex of 18, co-authored 100 publications receiving 4483 citations. Previous affiliations of J.M.G. Sá da Costa include Polytechnic Institute of Lisbon & Instituto Superior Técnico.

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The ATLAS Experiment at the CERN Large Hadron Collider

Georges Aad, +3032 more
TL;DR: The ATLAS detector as installed in its experimental cavern at point 1 at CERN is described in this paper, where a brief overview of the expected performance of the detector when the Large Hadron Collider begins operation is also presented.
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Approaches for dynamic modelling of flexible manipulator systems

TL;DR: In this article, a dynamic modelling of flexible manipulator systems with different mechanical structures and actuation mechanisms is presented, based on the assumed modes method considering linear displacements, quadratic displacements and the finite element method.
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Vibration control of a very flexible manipulator system

TL;DR: In this paper, the authors present experimental investigations into the development of feedforward and feedback control schemes for vibration control of a very flexible and high-friction manipulator system, based on input shaping and low-pass filtering techniques and a strain feedback control scheme.
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Soft Computing Approaches to Fault Diagnosis for Dynamic Systems

TL;DR: The paper provides many powerful examples of the use of SC methods for achieving good detection and isolation of faults in the presence of uncertain plant behaviour, together with their practical value for fault diagnosis of real process systems.
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Distributed supply chain management using ant colony optimization

TL;DR: A new supply chain management technique is introduced, based on modeling a generic supply chain with suppliers, logistics and distributers, as a distributed optimization problem, which allows the exchange of information between different optimization problems by means of a pheromone matrix.