A data-mining based methodology for wind forecasting

In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.

Da formação inicial à inserção na profissão

Dissertação apresentada à Escola Superior de Educação de Lisboa Para a obtenção do Grau de Mestre em Ciências da Educação - Especialidade Supervisão em Educação

Accounting logic and new professional in healthcare: a case study

The central place hospitals occupy in health systems transforms them into prime target of healthcare reforms. This study aims to identify current trends in organizational structure change in public hospitals and explore the role of accounting in attempts to develop controls over professionals within public hospitals. The analytical framework we proposed crosses the concept of “new professionalism” (Evetts, 2010), with the concept of “accounting logic” for controlling professionals (Broadbent and Laughlin, 1995). Looking for a more holistic overview, we developed a qualitative and exploratory study. The data were collected trough semi-structured interviews with doctors of a clinical hospital unit. Content analysis suggests that, although we cannot say that there is a complete and generalized integration of accounting information in the clinical decisions, important improvement has been made in that area. Despite the extensive literature developed on this topic, there is any empirical studies of authors are aware that allow us to realize how real doctors in reals day-to-day work integrated these trends of change in theirs clinical decisions.

Previsão de vento baseado em técnicas de Data Mining

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

On cluster analysis of complex and heterogeneous data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Clustering an interval data set : are the main partitions similar to a priori partition?

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

Mining protein structure data

The principal topic of this work is the application of data mining techniques, in particular of machine learning, to the discovery of knowledge in a protein database. In the first chapter a general background is presented. Namely, in section 1.1 we overview the methodology of a Data Mining project and its main algorithms. In section 1.2 an introduction to the proteins and its supporting file formats is outlined. This chapter is concluded with section 1.3 which defines that main problem we pretend to address with this work: determine if an amino acid is exposed or buried in a protein, in a discrete way (i.e.: not continuous), for five exposition levels: 2%, 10%, 20%, 25% and 30%. In the second chapter, following closely the CRISP-DM methodology, whole the process of construction the database that supported this work is presented. Namely, it is described the process of loading data from the Protein Data Bank, DSSP and SCOP. Then an initial data exploration is performed and a simple prediction model (baseline) of the relative solvent accessibility of an amino acid is introduced. It is also introduced the Data Mining Table Creator, a program developed to produce the data mining tables required for this problem. In the third chapter the results obtained are analyzed with statistical significance tests. Initially the several used classifiers (Neural Networks, C5.0, CART and Chaid) are compared and it is concluded that C5.0 is the most suitable for the problem at stake. It is also compared the influence of parameters like the amino acid information level, the amino acid window size and the SCOP class type in the accuracy of the predictive models. The fourth chapter starts with a brief revision of the literature about amino acid relative solvent accessibility. Then, we overview the main results achieved and finally discuss about possible future work. The fifth and last chapter consists of appendices. Appendix A has the schema of the database that supported this thesis. Appendix B has a set of tables with additional information. Appendix C describes the software provided in the DVD accompanying this thesis that allows the reconstruction of the present work.

Sistema de Torre de Refrigeração

Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química

Integration of e-learning systems with repositories of learning objects

This paper describes a communication model to integrate repositories of programming problems with other e-Learning software components. The motivation for this work comes from the EduJudge project that aims to connect an existing repository of programming problems to learning management systems. When trying to use the existing repositories of learning objects we realized that they are mainly specialized search engines and lack features for integration with other e-Learning systems. With this model we intend to clarify the main features of a programming problem repository, in order to enable the design and development of software components that use it. The two main points of this model are the definition of programming problems as learning objects and the definition of the core functions exposed by the repository. In both cases, this model follows the existing specifications of the IMS standard and proposes extensions to deal with the special requirements of automatic evaluation and grading of programming exercises. In the definition of programming problems as learning objects we introduced a new schema for meta-data. This schema is used to represent meta-data related to automatic evaluation that cannot be conveniently represented using the standard: the type of automatic evaluation; the requirements of the evaluation engine; or the roles of different assets - tests cases, program solutions, etc. In the definition of the core functions we used two different web services flavours - SOAP and REST - and described each function as an operation for each type of interface. We describe also the data types of the arguments of each operation. These data types consist mainly on learning objects and their identifications, but include also usage reports and queries using XQuery.

Estimation of vegetation carbon stock in Portugal using land use/ land cover data

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

A Passagem do 1.º para o 2.º CEB. Continuidade ou Recomeço?

Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino do 1.º e do 2.º Ciclo de Educação Básica

A metodologia BIM-FM aplicada a um caso prático

O crescente aumento da consciencialização da importância da fase de operação e manutenção, bem como a amplificação que a metodologia Building Information Modelling (BIM) tem obtido nos últimos anos, sugere uma necessidade de alterar a atual abordagem da gestão das instalações de forma a dotá-la das mais recentes inovações tecnológicas como seja a utilização do BIM. Os Building Information Models apresentam as características ideais para a integração da gestão das instalações, não só pela visualização do edifício, mas sobretudo pela potencialidade que a base de dados oferece, com informação referente a cada um dos componentes presentes e suas relações. O âmbito deste trabalho envolve assim a integração da gestão das instalações com o modelo BIM criado, representativo do edifício em estudo. Este trabalho começa com as definições do âmbito e dos objetivos que são propostos no Capítulo 1. No Capítulo 2, é elaborada uma pesquisa sobre o estado da arte atual de cada uma das metodologias BIM e FM, de forma a tomar conhecimento dos seus conceitos principais. Foi feito também um levantamento no campo do BIM-FM de forma a apurar as atuais soluções tecnológicas existentes, a forma como é feita a sua troca de informação e também alguns casos em que esta metodologia foi aplicada. Com base na informação recolhida sobre as metodologias e também nos casos práticos estudados, é realizado no Capítulo 3, capítulo central deste trabalho, a aplicação prática. A realização desta aplicação é dividida por 3 fases principais. Numa primeira fase é especificada e recolhida a informação necessária de ser obtida para a realização do modelo e a posterior aplicação do FM. A escolha da informação a recolher é feita ponderando todos os fatores existentes, mas de forma a cumprir os requisitos pedidos. Numa segunda fase, assente na compilação de informação recolhida anteriormente, realiza-se o modelo do edifício. A modelação, de forma a seguir o método de trabalho BIM é realizada por especialidades, sendo numa primeira fase realizada a especialidade de arquitetura e posteriormente, utilizando esse modelo como base, é feita a modelação das especialidades de águas, águas residuais, AVAC e eletricidade. Esta escolha foi também estimulada pela organização do software utilizado para a modelação, por módulos. Na última fase da aplicação do caso prático a informação inserida na fase de modelação do edifício é exportada para o software de FM, neste caso em específico, o IBM Maximo. Para a exportação destes dados foi utilizado o formato Construction Operations Building Information Exchange (COBie), de forma a garantir a integridade e conformidade da informação transferida. No Capítulo 4 deste trabalho são abordadas as especificidades relativas à informação existente, à modelação e à troca de dados entre o software de modelação e o software utilizado na gestão do edifício. São também sugeridos alguns temas para futuros desenvolvimentos com o intuito de ampliação dos campos de FM com o uso do modelo. O BIM-FM é um tema emergente na atualidade do BIM, sendo a sua utilização encarada como uma mais-valia ao processo BIM. A compilação da informação durante a fase de projeto e execução, aliada à existência do modelo torna a implementação do FM com o modelo BIM como uma sequência natural.

Integration of e-portfolios in learning management systems

The LMS plays a decisive role in most eLearning environments. Although they integrate many useful tools for managing eLearning activities, they must also be effectively integrated with other specialized systems typically found in an educational environment such as Repositories of Learning Objects or ePortfolio Systems. Both types of systems evolved separately but in recent years the trend is to combine them, allowing the LMS to benefit from using the ePortfolio assessment features. This paper details the most common strategies for integrating an ePortfolio system into an LMS: the data, the API and the tool integration strategies. It presents a comparative study of strategies based on the technical skills, degree of coupling, security features, batch integration, development effort, status and standardization. This study is validated through the integration of two of the most representative systems on each category - respectively Mahara and Moodle.