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Publications

Publications by Hugo Miguel Ferreira

2018

Using metalearning for parameter tuning in neural networks

Authors
Felix, C; Soares, C; Jorge, A; Ferreira, H;

Publication
Lecture Notes in Computational Vision and Biomechanics

Abstract
Neural networks have been applied as a machine learning tool in many different areas. Recently, they have gained increased attention with what is now called deep learning. Neural networks algorithms have several parameters that need to be tuned in order to maximize performance. The definition of these parameters can be a difficult, extensive and time consuming task, even for expert users. One approach that has been successfully used for algorithm and parameter selection is metalearning. Metalearning consists in using machine learning algorithm on (meta)data from machine learning experiments to map the characteristics of the data with the performance of the algorithms. In this paper we study how a metalearning approach can be used to obtain a good set of parameters to learn a neural network for a given new dataset. Our results indicate that with metalearning we can successfully learn classifiers from past learning tasks that are able to define appropriate parameters. © 2018, Springer International Publishing AG.

2017

A pilot for proactive maintenance in industry 4.0

Authors
Ferreira, LL; Albano, M; Silva, J; Martinho, D; Marreiros, G; Di Orio, G; Malo, P; Ferreira, H;

Publication
IEEE International Workshop on Factory Communication Systems - Proceedings, WFCS

Abstract
The reliability and safety of industrial machines depends on their timely maintenance. The integration of Cyber Physical Systems within the maintenance process enables both continuous machine monitoring and the application of advanced techniques for predictive and proactive machine maintenance. The building blocks for this revolution-embedded sensors, efficient preprocessing capabilities, ubiquitous connection to the internet, cloud-based analysis of the data, prediction algorithms, and advanced visualization methods- A re already in place, but several hurdles have to be overcome to enable their application in real scenarios, namely: The integration with existing machines and existing maintenance processes. Current research and development efforts are building pilots and prototypes to demonstrate the feasibility and the merits of advanced maintenance techniques, and this paper describes a system for the industrial maintenance of sheet metal working machinery and its evolution towards a full proactive maintenance system. © 2017 IEEE.

2012

Environmental modeling with precision navigation using ROAZ autonomous surface vehicle

Authors
Hugo Miguel Ferreira; Carlos Almeida; Alfredo Martins; José Miguel Almeida; André Dias; Guilherme Silva; Eduardo Silva

Publication
IROS 2012 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Portugal

Abstract
The use of robotic vehicles for environmental modeling is discussed. This paper presents diverse results in autonomous marine missions with the ROAZ autonomous surface vehicle. The vehicle can perform autonomous missions while gathering marine data with high inertial and positioning precision. The underwater world is an, economical and environmental, asset that need new tools to study and preserve it. ROAZ is used in marine environment missions since it can sense and monitor the surface and underwater scenarios. Is equipped with a diverse set of sensors, cameras and underwater sonars that generate 3D environmental models. It is used for study the marine life and possible underwater wrecks that can pollute or be a danger to marine navigation. The 3D model and integration of multibeam and sidescan sonars represent a challenge in nowadays. Adding that it is important that robots can explore an area and make decisions based on their surroundings and goals. Regard that, autonomous robotic s

2001

Integration Infrastructures: Bridging the Gap to the Extended Enterprise

Authors
Hugo Miguel Mendes Ferreira; João José Pinto Ferreira

Publication
CARS&FOF'2001 - 17th ISPE/IFAC International Conference on CAD/CAM, Robotics and Factories of the Future, Durban, South Africa

Abstract

2007

Community Knowledge Sharing: issues on the use of ontologies

Authors
Hugo Ferreira; António Lucas Soares

Publication
in proceedings of EPIA 2007 - 13th EPIA International Conference - Portuguese Conference on Artifical Intelligence, Guimarães, Portugal

Abstract
Enterprise sponsored virtual communities (ESVC) are emerging as a serious business schemes fostering, at the intra and inter-organizational level, collaboration and knowledge sharing. This community paradigm is taking place among or complementing the more established forms of inter-organizational interaction such as chains or networks. ESVCs are complex socio-technical systems, difficult to design and maintain, needing multi-disciplinary approaches for their development. This paper presents a case in the development of a knowledge community support system in the context of an Industrial Association Group (IAG) in the construction sector. This article discusses the various complex issues encountered during its design and development. Hopefully this discussion will be of use to those that are not only embarking on such projects but also those who research and develop the tools and frameworks required for the development of real-life semantic web applications.

2006

AN INTEGRATED LIFE CYCLE FOR WORKFLOW MANAGEMENT BASED ON LEARNING AND PLANNING

Authors
Hugo Ferreira; Diogo Ferreira

Publication
IJCIS - International Journal of Computational Intelligence Systems, vol.15, no.4, pp.485

Abstract
The ability to describe business processes as executable models has always been one of the fundamental premises of workflow management. Yet, the tacit nature of human knowledge is often an obstacle to eliciting accurate process models. On the other hand, the result of process modeling is a static plan of action, which is difficult to adapt to changing procedures or to different business goals. In this article, we attempt to address these problems by approaching workflow management with a combination of learning and planning techniques. Assuming that processes cannot be fully described at build-time, we make use of learning techniques, namely Inductive Logic Programming (ILP), in order to discover workflow activities and to describe them as planning operators. These operators will be subsequently fed to a partial-order planner in order to find the process model as a planning solution. The continuous interplay between learning, planning and execution aims at arriving at a feasible plan b

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