DME - Artigos em Revistas Internacionais / Articles in International Journals
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- An Approach to Variable Aggregation in Efficiency AnalysisPublication . Noncheva, Veska; Mendes, Armando B.; Silva, EmilianaIn the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.
- Behaviors and attitudes in the teaching and learning of geometryPublication . Melo, Helena Sousa; Martins, Maria do CarmoThis paper presents a case study about teaching and learning topics of Geometry that are part of the syllabus of high school courses. Internationally the teaching of Geometry has been the subject of several studies. Nevertheless, research continues to reveal that Geometry is still quite absent from the classrooms, especially in the early years; Geometry is disliked by most students, is misunderstood, and its notation is totally ignored. One of the reasons for this failure is that these issues are addressed superficially in the curriculum of the training teachers of Geometry. This paper describes the experience of teaching Geometry to a class with 90 students in academic year 2014-2015, enumerates some difficulties and behaviors faced by students and teachers, and exposes the results of the academic success.
- Big Data in SATA Airline : finding new solutions for old problemsPublication . Mendes, Armando B.; Guerra, Hélia; Gomes, Luís Mendes; Oliveira, Ângelo; Cavique, LuísWith the rapid growth of operational data needed in airlines and the value that can be attributed to knowledge extracted from these data, airlines have already realized the importance of technologies and methodologies associated with the concept of big data. In this article, we present the case study of SATA Airlines. The operational and the decision support systems are described as well as the perspectives of using these new technologies to support knowledge creation and aid the solution of problems in this specific company. The proposed system provides a new operational environment.
- Cluster Analysis of Business DataPublication . Sousa, Áurea; Bacelar-Nicolau, Helena; Silva, OsvaldoIn this work, classical as well as probabilistic hierarchical clustering models are used to look for typologies of variables in classical data, typologies of groups of individuals in a classical three-way data table, and typologies of groups of individuals in a symbolic data table. The data are issued from a questionnaire on business area in order to evaluate the quality and satisfaction with the services provided to customers by an automobile company. The Ascendant Hierarchical Cluster Analysis (AHCA) is based, respectively, on the basic affinity coefficient and on extensions of this coefficient for the cases of a classical three-way data table and a symbolic data table, obtained from the weighted generalized affinity coefficient. The probabilistic aggregation criteria used, under the probabilistic approach named VL methodology (V for Validity, L for Linkage), resort essentially to probabilistic notions for the definition of the comparative functions. The validation of the obtained partitions is based on the global statistics of levels (STAT).
- Cluster analysis using affinity aoefficient in order to identify religious beliefs profilesPublication . Sousa, Áurea; Nicolau, Fernando C.; Bacelar-Nicolau, Helena; Silva, OsvaldoWe present an application of Ascendant Hierarchical Cluster Analysis (AHCA) to a dataset related to religion, in order to find a typology of religious beliefs profiles of individuals who live on São Miguel island (Azores) according to the frequency they go to the Mass. AHCA was based on the weighted generalized affinity coefficient for symbolic or complex data, and on classical and probabilistic aggregation criteria; the probabilistic ones belong to a parametric family of methods in the scope of the VL methodology. Additionally, we applied some validation measures (based on the values of the proximity matrix and adapted for the case of similarity measures) to evaluate the obtained results (clusters and partitions).
- Clustering an interval data set : are the main partitions similar to a priori partition?Publication . Sousa, Áurea; Bacelar-Nicolau, Helena; Nicolau, Fernando C.; Silva, OsvaldoIn this paper we compare the best partitions of data units (cities) obtained from different algorithms of Ascendant Hierarchical Cluster Analysis (AHCA) of a well-known data set of the literature on symbolic data analysis (“city temperature interval data set”) with a priori partition of cities given by a panel of human observers. The AHCA was based on the weighted generalised affinity with equal weights, and on the probabilistic coefficient associated with the asymptotic standardized weighted generalized affinity coefficient by the method of Wald and Wolfowitz. These similarity coefficients between elements were combined with three aggregation criteria, one classical, Single Linkage (SL), and the other ones probabilistic, AV1 and AVB, the last ones in the scope of the VL methodology. The evaluation of the partitions in order to find the partitioning that best fits the underlying data was carried out using some validation measures based on the similarity matrices. In general, global satisfactory results have been obtained using our methods, being the best partitions quite close (or even coinciding) with the a priori partition provided by the panel of human observers.
- Clustering of Symbolic Data based on Affinity Coefficient: Application to a Real Data SetPublication . Sousa, Áurea; Bacelar-Nicolau, Helena; Nicolau, Fernando C.; Silva, OsvaldoIn this paper, we illustrate an application of Ascendant Hierarchical Cluster Analysis (AHCA) to complex data taken from the literature (interval data), based on the standardized weighted generalized affinity coefficient, by the method of Wald and Wolfowitz. The probabilistic aggregation criteria used belong to a parametric family of methods under the probabilistic approach of AHCA, named VL methodology. Finally, we compare the results achieved using our approach with those obtained by other authors.
- Clustering of variables with a three-way approach for health sciencesPublication . Bacelar-Nicolau, Helena; Nicolau, Fernando C.; Sousa, Áurea; Bacelar-Nicolau, LeonorCluster analysis or classification usually concerns a set of exploratory multivariate data analysis methods and techniques for grouping either a set of statistical data units or the associated set of descriptive variables, into clusters of similar and, hopefully, well separated elements. In this work we refer to an extension of this paradigm to generalized three-way data representations and particularly to classification of interval variables. Such approach appears to be especially useful in large data bases, mostly in a data mining context. A health sciences case study is partially discussed.
- Clustering supermarkets: the role of expertsPublication . Mendes, Armando B.; Cardoso, Margarida G.M.S.This work is part of a supermarket chain expansion study and is intended to cluster the existent outlets in order to support the evaluation of outlet performance and new outlet site location. To overcome the curse of dimensionality (a large number of attributes for a very small number of existing outlets) experts' knowledge is considered in the clustering process. Three alternative approaches are compared for this end, the experts being required to: (1) a priori: provide values for perceived dissimilarities between pairs of outlets; (2) a posteriori: evaluate results from alternative regression trees; (3) interactively: help to select base variables and evaluate results from alternative dendrograms. The later approach provided the best results according to the marketing experts.
- Da resolução de problemas à explicitação do raciocínio matemático : uma experiência em contexto de estágioPublication . Cascalho, José Manuel; Teixeira, Ricardo Emanuel Cunha; Ferreira, Rui Filipe MeirelesA resolução de problemas é um processo fundamental na aprendizagem da matemática. Neste artigo, apresenta-se uma reflexão sobre a importância deste processo matemático e de como ele pode ser conduzido de forma a estimular o raciocínio matemático através da promoção da comunicação, em contexto de sala de aula. O trabalho foi realizado na etapa final de formação de educadores e professores no contexto do pré-escolar e do primeiro ciclo do ensino básico. Em resultado das atividades realizadas, discute-se o papel da utilização de uma heurística ao longo da resolução de problemas, a importância na escolha de estratégia para a interação com os alunos, bem como o desenho intencional de materiais didáticos. A experiência enquadra-se numa abordagem qualitativa de design de experiência de ensino.