O teatro na comunidade de Torres Vedras: as práticas de criação e de fruição em torno do grupo do Grémio Artístico Torreense

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Artística - Especialização em Teatro na Educação

A entrada na profissão do educador de infância: percursos singulares

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção do grau de Mestre em Ciências da Educação - Especialidade Supervisão em Educação

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.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Inclusão e práticas de diferenciação curricular nos cursos de educação e formação

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, especialidade em Educação Especial, ramo de Problemas de Cognição e Multideficiência

Power systems reliability calculation based on fuzzy data mining

This paper presents a methodology supported on the data base knowledge discovery process (KDD), in order to find out the failure probability of electrical equipments’, which belong to a real electrical high voltage network. Data Mining (DM) techniques are used to discover a set of outcome failure probability and, therefore, to extract knowledge concerning to the unavailability of the electrical equipments such us power transformers and high-voltages power lines. The framework includes several steps, following the analysis of the real data base, the pre-processing data, the application of DM algorithms, and finally, the interpretation of the discovered knowledge. To validate the proposed methodology, a case study which includes real databases is used. This data have a heavy uncertainty due to climate conditions for this reason it was used fuzzy logic to determine the set of the electrical components failure probabilities in order to reestablish the service. The results reflect an interesting potential of this approach and encourage further research on the topic.

Data mining applications in power systems - case-studies and future trends

Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

Zonal prices analysis supported by a data mining based methodology

A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

Online versus postal questionnaires: a comparison between two data collection methods

Objectives : The purpose of this article is to find out differences between surveys using paper and online questionnaires. The author has deep knowledge in the case of questions concerning opinions in the development of survey based research, e.g. the limits of postal and online questionnaires. Methods : In the physician studies carried out in 1995 (doctors graduated in 1982-1991), 2000 (doctors graduated in 1982-1996), 2005 (doctors graduated in 1982-2001), 2011 (doctors graduated in 1977-2006) and 457 family doctors in 2000, were used paper and online questionnaires. The response rates were 64%, 68%, 64%, 49% and 73%, respectively. Results : The results of the physician studies showed that there were differences between methods. These differences were connected with using paper-based questionnaire and online questionnaire and response rate. The online-based survey gave a lower response rate than the postal survey. The major advantages of online survey were short response time; very low financial resource needs and data were directly loaded in the data analysis software, thus saved time and resources associated with the data entry process. Conclusions : The current article helps researchers with planning the study design and choosing of the right data collection method.

Programa Minha Casa Minha Vida: a construção social de um mercado

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Os desafios da inclusão de alunos com síndrome de down

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

Parcerias logisticas: estudos de caso

O processo de globalização tem contribuído para o desenvolvimento da reestruturação das firmas, por vezes são necessárias alianças, o que implica alterações na cadeia de valor, sendo fundamentais novas formas de relacionamento interpessoal e de operação. Os Pólos Industriais representam a presença física de entidades em determinadas posições geográficas, responsáveis pelo desenvolvimento económico, tecnológico e social da região. Este trabalho de investigação tem como intuito geral verificar o contributo efetivo para o aumento de vantagem competitiva das firmas parceiras na logística e produção de componentes para o setor automóvel, tendo como estudo do caso Caetano Coatings Automotive. O estudo foi realizado no Pólo Industrial do Carregado, com base numa pesquisa empírica, cumulativamente com revisão da literatura inerente às parcerias em cluster no sector automóvel e várias visitas ao local. Para a realização deste objetivo foi utilizado o método do estudo do caso por permitir ao investigador através da observação direta e entrevista analisar fenómenos atuais. Tal recolha de dados demonstra que alterações de localização e o fator proximidade contribuem para aumento de competitividade do Pólo Industrial através da redução do espaço e tempo e consequentemente redução de custos e lead-time. Foram analisadas de forma comparativa o desenvolvimento das firmas que detinham e detêm parcerias no Pólo Industrial, tendo sido identificado de forma significativa as contribuições para o aumento da vantagem competitiva. Os resultados obtidos evidenciam fatores que contribuem para novos tipos de relacionamento e aumento de vantagem competitiva foi devida à deslocalização das firmas parceiras integradas no Pólo Industrial.

SmartClean: an incremental data cleaning tool

This paper presents the SmartClean tool. The purpose of this tool is to detect and correct the data quality problems (DQPs). Compared with existing tools, SmartClean has the following main advantage: the user does not need to specify the execution sequence of the data cleaning operations. For that, an execution sequence was developed. The problems are manipulated (i.e., detected and corrected) following that sequence. The sequence also supports the incremental execution of the operations. In this paper, the underlying architecture of the tool is presented and its components are described in detail. The tool's validity and, consequently, of the architecture is demonstrated through the presentation of a case study. Although SmartClean has cleaning capabilities in all other levels, in this paper are only described those related with the attribute value level.

Ontologies for reusing data cleaning knowledge

The emergence of new business models, namely, the establishment of partnerships between organizations, the chance that companies have of adding existing data on the web, especially in the semantic web, to their information, led to the emphasis on some problems existing in databases, particularly related to data quality. Poor data can result in loss of competitiveness of the organizations holding these data, and may even lead to their disappearance, since many of their decision-making processes are based on these data. For this reason, data cleaning is essential. Current approaches to solve these problems are closely linked to database schemas and specific domains. In order that data cleaning can be used in different repositories, it is necessary for computer systems to understand these data, i.e., an associated semantic is needed. The solution presented in this paper includes the use of ontologies: (i) for the specification of data cleaning operations and, (ii) as a way of solving the semantic heterogeneity problems of data stored in different sources. With data cleaning operations defined at a conceptual level and existing mappings between domain ontologies and an ontology that results from a database, they may be instantiated and proposed to the expert/specialist to be executed over that database, thus enabling their interoperability.

Epidemiology of physiotherapy utilization among adults and elderly

OBJECTIVE: To analyze the prevalence of physiotherapy utilization and to explore the variables associated to its utilization. METHODS: A population-based cross-sectional study, including 3,100 subjects aged 20 years or more living in the urban area of Pelotas, southern Brazil, was carried out. The sample was selected following a multiple-stage protocol; the census tracts delimited by the Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics) were the primary sample units. Following descriptive and crude analyses, Poisson regression models taking the clustering of the sample into account were carried out. Data were collected through face-to-face interviews using a standardized and pre-tested questionnaire. RESULTS: The lifetime utilization of physiotherapy was 30.2%; and physiotherapy utilization in the 12 months prior to the interview was reported by 4.9%. Women, elderly subjects, and those from higher socioeconomic levels were more likely to use physiotherapy. Restricting analysis to subjects who attended physiotherapy, 66% used public health services, 25% used insurance health services and 9% had private sessions. CONCLUSIONS: This is the first population-based study on physiotherapy utilization carried out in Brazil. Utilization of physio therapy was lower than reported in both developed and developing countries. The study findings might help public health authorities to organize healthcare service in terms of this important demand.