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Publicações

2014

WISE'14, Proceedings of the 2014 ACM International Workshop on Long-term Industrial Collaboration on Software Engineering, Vasteras, Sweden, September 16, 2014

Autores
Dobrin, R; Wallin, P; Paiva, ACR; Cohen, MB;

Publicação
WISE@ASE

Abstract

2014

Geometrical models and algorithms for irregular shapes placement problems

Autores
Pedro Filipe de Monteiro Rocha;

Publicação

Abstract

2014

Analysis on the selection of course and institution of engineering students [Análise sobre a escolha do curso e instituição dos estudantes da Área de engenharia]

Autores
Barros, D; Vasconcelos, R; Costa, AP; Reis, LP; Faria, BM;

Publicação
Iberian Conference on Information Systems and Technologies, CISTI

Abstract
Every year thousands of students apply for access to higher education in Portuguese universities. These students are allocated according to their application, secondary school grades and their preference to distinct establishment-course pairs. Despite official statistics provided by the Ministry of Science, Technology and Higher Education (MCTES), it is not always possible to have the relevant indicators for universities make a good decision concerning courses and vacancies to offer. This study evaluates the factors that influence students in their choice of a pair establishment-course as well as understand the different variables that are related to the same attribution of influence. The study is observational and empirical using questionnaires, with the appropriate statistical analysis. The results showed a relation in greater number among the studied factors and gender. In conclusion the prestige of the institution, employment and intellectual development are the factors most valued by students. © 2014 AISTI.

2014

MetaStream: A meta-learning based method for periodic algorithm selection in time-changing data

Autores
Debiaso Rossi, ALD; de Leon Ferreira de Carvalho, ACPDF; Soares, C; de Souza, BF;

Publicação
NEUROCOMPUTING

Abstract
Dynamic real-world applications that generate data continuously have introduced new challenges for the machine learning community, since the concepts to be learned are likely to change over time. In such scenarios, an appropriate model at a time point may rapidly become obsolete, requiring updating or replacement. As there are several learning algorithms available, choosing one whose bias suits the current data best is not a trivial task. In this paper, we present a meta-learning based method for periodic algorithm selection in time-changing environments, named MetaStream. It works by mapping the characteristics extracted from the past and incoming data to the performance of regression models in order to choose between single learning algorithms or their combination. Experimental results for two real regression problems showed that MetaStream is able to improve the general performance of the learning system compared to a baseline method and an ensemble-based approach.

2014

Explosion of smoothness for conjugacies between multimodal maps

Autores
Alves, JF; Pinheiro, V; Pinto, AA;

Publicação
JOURNAL OF THE LONDON MATHEMATICAL SOCIETY-SECOND SERIES

Abstract
Let f and g be smooth multimodal maps with no periodic attractors and no neutral points. If a topological conjugacy h between f and g is C-1 at a point in the nearby expanding set of f, then h is a smooth diffeomorphism in the basin of attraction of a renormalization interval of f. In particular, if f:I -> I and g : J -> J are C-r unimodal maps and h is C-1 at a boundary of I, then h is C-r in I.

2014

Selected contributions from the Open Source Software Certification (OpenCert) workshops Preface

Autores
Barbosa, LS; Shaikh, SA;

Publicação
SCIENCE OF COMPUTER PROGRAMMING

Abstract

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