2017
Authors
Choobdar, S; Pinto Ribeiro, PM; Silva, FMA;
Publication
SAC
Abstract
The structural patterns in the neighborhood of nodes assign unique roles to the nodes. Mining the set of existing roles in a network provides a descriptive profile of the network and draws its general picture. This paper proposes a new method to determine structural roles in a dynamic network based on the current position of nodes and their historic behavior. We develop a temporal ensemble clustering technique to dynamically find groups of nodes, holding similar tempo-structural roles. We compare two weighting functions, based on age and distribution of data, to incorporate temporal behavior of nodes in the role discovery. To evaluate the performance of the proposed method, we assess the results from two points of view: 1) goodness of fit to current structure of the network; 2) consistency with historic data. We conduct the evaluation using different ensemble clustering techniques. The results on real world networks demonstrate that our method can detect tempo-structural roles that simultaneously depict the topology of a network and reflect its dynamics with high accuracy.
2017
Authors
Rocha, C; Mendonca, T; Silva, ME; Gambus, P;
Publication
JOURNAL OF CLINICAL MONITORING AND COMPUTING
Abstract
2017
Authors
Coelho, JP; Pinho, TM; Boaventura Cunha, J; de Oliveira, JB;
Publication
IFAC PAPERSONLINE
Abstract
The brain emotional learning (BEL) control paradigm has been gathering increased interest by the control systems design community. However, the lack of a consistent mathematical formulation and computer based tools are factors that have prevented its more widespread use. In this article both features are tackled by providing a coherent mathematical framework for both the continuous and discrete-time formulations and by presenting a SIMULINK (R) computational tool that can be easily used for fast prototyping BEL based control systems.
2017
Authors
Teles, MD; de Sousa, JF;
Publication
19TH EURO WORKING GROUP ON TRANSPORTATION MEETING (EWGT2016)
Abstract
This paper presents a General Morphological Analysis (GMA) meta-model aiming to help decision-makers wishing to integrate sustainability concerns into the company strategy. This is made by joining Operational Research (OR) analysts, decision-makers and stakeholders as participants in the problem structuring and formulation process. This is particularly relevant in societal issues, where public transport companies are particularly important. Indeed, public transport companies play a quite visible role in the dimensions of corporate social responsibility, namely because of four reasons: (i) they provide daily services crucial to mass customers' mobility; (ii) their investments are usually of high value and rather sensitive to technological development; (iii) they play a crucial role in the energy sector and (iv) are strongly dependent upon macro-policies. © 2017 The Authors. Published by Elsevier B.V.
2017
Authors
Melo, P; Araújo, RE;
Publication
TECHNICAL INNOVATION FOR SMART SYSTEMS (DOCEIS 2017)
Abstract
The design of efficient and high power density electrical machines needs an accurate characterization of magnetic phenomena. Core losses estimation is usually addressed by empirical models, where its lack of accuracy is well known. Hysteresis models are able to take an insight into the magnetic physical mechanisms. Compared to the empirical models, they contribute to a higher accuracy in modeling electromagnetic systems, including core losses estimation. At a macroscopic level, two models are often used: the Preisach and the Jiles-Atherton (J-A) models. This paper presents their basic formulation, as well the main limitations and scope of application. This is a first step to investigate the possible application of hysteresis models, in order to reach accurate core losses estimation in switched reluctance machines.
2017
Authors
Azevedo Perdicoúlis, TP; Almeida, R; Lopes dos Santos, P; Jank, G;
Publication
Lecture Notes in Electrical Engineering
Abstract
In this paper we design a model based method to locate a leakage and estimate its size in a gas network, using a linearised version of an hyperbolic PDE. To do this, the problem is reduced to two identical ODEs, allowing in this way for a representation of the pressure as well as the mass flow in terms of its system of fundamental solutions. Then using the available measurements at the grid boundary points, the correspondent coefficients can be determined. Assuming pressure continuity, we check for consistency of the coefficients in order to find faulty pipelines. Thence, the location of the leakage can be found either graphically or using a numerical method for a specific pipe. Next, its size can also be estimated. © Springer International Publishing Switzerland 2017.
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