951 resultados para aproximate common knowledge
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Paper to be presented at the ESREA Conference Learning to Change? The Role of Identity and Learning Careers in Adult Education, 7-8 December, 2006, Université Catholique Louvain, Louvain–la-Neuve, Belgium
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Versão editor: http://www.isegi.unl.pt/docentes/acorreia/documentos/European_Challenge_KM_Innovation_2004.pdf
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Paper presented at Information Resources Management Association International Conference, in Philadelphia (PA), 18-21 May 2003
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Paper accepted for the OKLC 2009 - International Conference on Organizational Learning, Knowledge and Capabilities (26-28th, April 2009, Amsterdam, the Netherlands).
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The purpose of this paper is to analyse if Multiple-Choice Tests may be considered an interesting alternative for assessing knowledge, particularly in the Mathematics area, as opposed to the traditional methods, such as open questions exams. In this sense we illustrate some opinions of the researchers in this area. Often the perception of the people about the construction of this kind of exams is that they are easy to create. But it is not true! Construct well written tests it’s a hard work and needs writing ability from the teachers. Our proposal is analyse the construction difficulties of multiple - choice tests as well some advantages and limitations of this type of tests. We also show the frequent critics and worries, since the beginning of this objective format usage. Finally in this context some examples of Multiple-Choice Items in the Mathematics area are given, and we illustrate as how we can take advantage and improve this kind of tests.
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This essay sees “through” an object produced by Portuguese folklore: the moliceiro boat of Ria de Aveiro, whose most original characteristic is the group of four different panels painted on each boat. These unique panels have echoed national mythologies and have undergone influence from institutional channels of instruction and propaganda for much of the twentieth century. We will analyse how this boat expresses the inventory of a community’s identity, imagination, and practices.
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In the management of solid waste, pollutants over a wide range are released with different routes of exposure for workers. The potential for synergism among the pollutants raises concerns about potential adverse health effects, and there are still many uncertainties involved in exposure assessment. In this study, conventional (culture-based) and molecular real-time polymerase chain reaction (RTPCR) methodologies were used to assess fungal air contamination in a waste-sorting plant which focused on the presence of three potential pathogenic/toxigenic fungal species: Aspergillus flavus, A. fumigatus, and Stachybotrys chartarum. In addition, microbial volatile organic compounds (MVOC) were measured by photoionization detection. For all analysis, samplings were performed at five different workstations inside the facilities and also outdoors as a reference. Penicillium sp. were the most common species found at all plant locations. Pathogenic/toxigenic species (A. fumigatus and S. chartarum) were detected at two different workstations by RTPCR but not by culture-based techniques. MVOC concentration indoors ranged between 0 and 8.9 ppm (average 5.3 ± 3.16 ppm). Our results illustrated the advantage of combining both conventional and molecular methodologies in fungal exposure assessment. Together with MVOC analyses in indoor air, data obtained allow for a more precise evaluation of potential health risks associated with bioaerosol exposure. Consequently, with this knowledge, strategies may be developed for effective protection of the workers.
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7th Mediterranean Conference on Information Systems, MCIS 2012, Guimaraes, Portugal, September 8-10, 2012, Proceedings Series: Lecture Notes in Business Information Processing, Vol. 129
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The dominant discourse in education and training policies, at the turn of the millennium, was on lifelong learning (LLL) in the context of a knowledge-based society. As Green points (2002, pp. 611-612) several factors contribute to this global trend: The demographic change: In most advanced countries, the average age of the population is increasing, as people live longer; The effects of globalisation: Including both economic restructuring and cultural change which have impacts on the world of education; Global economic restructuring: Which causes, for example, a more intense demand for a higher order of skills; the intensified economic competition, forcing a wave of restructuring and creating enormous pressure to train and retrain the workforce In parallel, the “significance of the international division of labour cannot be underestimated for higher education”, as pointed out by Jarvis (1999, p. 250). This author goes on to argue that globalisation has exacerbated differentiation in the labour market, with the First World converting faster to a knowledge economy and a service society, while a great deal of the actual manufacturing is done elsewhere.
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Dissertação de Mestrado em Finanças Empresariais
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With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.
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This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.
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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.
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Mestrado em Fiscalidade
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A obesidade é apontada como o distúrbio nutricional mais frequente em crianças e adolescentes nos países desenvolvidos e a sua prevalência tem vindo a aumentar a nível mundial a um ritmo alarmante. Neste artigo, são apresentados três estudos que se coordenam entre si. No primeiro estudo, avalia-se a prevalência de pré-obesidade (22,6%) e de obesidade (7,8%) infantojuvenil em Portugal, apresentando valores superiores nos rapazes e nos adolescentes mais jovens. Em relação aos hábitos alimentares, verifica-se que o consumo de alimentos de características nutricionais de baixa qualidade é superior no grupo normoponderal. Em relação à atividade física, quanto maior o índice de atividade física menor o percentil de I.M.C. No estudo sobre determinantes parentais, salienta-se que a grande maioria dos pais das crianças com excesso de peso tendem a sub-avaliar o peso da criança. Outro aspeto relevante é a confirmação de que o conhecimento nutricional dos pais influencia claramente os hábitos alimentares das crianças. Por fim, é apresentado um projeto de intervenção que, intervindo nos determinantes parentais, visa a mudança das suas crenças e comportamentos, de modo a promoverem mudanças alimentares nos seus filhos.