897 resultados para Education approach to work


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Dissertação apresentada para obtenção do Grau de Doutor em Conservação e Restauro, especialidade Teoria, História e Técnicas, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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As the variety of mobile devices connected to the Internet growts there is a correponding increase in the need to deliver content tailored to their heterogeneous characteristics. At the same time, we watch to the increase of e-learning in universities through the adoption of electronic platforms and standards. Not surprisingly, the concept of mLearning (Mobile Learning) appeared in recent years decreasing the limitation of learning location with the mobility of general portable devices. However, this large number and variety of Web-enabled devices poses several challenges for Web content creators who want to automatic get the delivery context and adapt the content to the client mobile devices. In this paper we analyze several approaches to defining delivery context and present an architecture for deliver uniform mLearning content to mobile devices denominated eduMCA - Educational Mobile Content Adaptation. With the eduMCA system the Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.

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Trabalho de Projecto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Encenação.

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Mestrado em Engenharia Informática - Área de Especialização em Tecnologias do Conhecimento e Decisão

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This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

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Societal changes have, throughout history, pushed the long-established boundaries of education across all grade levels. Technology and media merge with education in a continuous complex social process with human consequences and effects. We, teachers, can aspire to understand and interpret this volatile context that is being redesigned at the same time society itself is being reshaped as a result of the technological evolution. The language- learning classroom is not impenetrable to these transformations. Rather, it can perhaps be seen as a playground where teachers and students gather to combine the past and the present in an integrated approach. We draw on the results from a previous study and argue that Digital Storytelling as a Process is capable of aggregating and fostering positive student development in general, as well as enhancing interpersonal relationships and self-knowledge while improving digital literacy. Additionally, we establish a link between the four basic language-learning skills and the Digital Storytelling process and demonstrate how these converge into what can be labeled as an integrated language learning approach.

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This study proposes a new methodology to increase the power delivered to any load point in a radial distribution network, through the identification of new investments in order to improve the repair time. This research work is innovative and consists in proposing a full optimisation model based on mixed-integer non-linear programming considering the Pareto front technique. The goal is to achieve a reduction in repair times of the distribution networks components, while minimising the costs of that reduction as well as non-supplied energy costs. The optimisation model considers the distribution network technical constraints, the substation transformer taps, and it is able to choose the capacitor banks size. A case study based on a 33-bus distribution network is presented in order to illustrate in detail the application of the proposed methodology.

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This work explores the use of fluorescent probes to evaluate the responses of the green alga Pseudokirchneriella subcapitata to the action of three nominal concentrations of Cd(II), Cr(VI), Cu(II) and Zn(II) for a short time (6 h). The toxic effect of the metals on algal cells was monitored using the fluorochromes SYTOX Green (SG, membrane integrity), fluorescein diacetate (FDA, esterase activity) and rhodamine 123 (Rh123, mitochondrial membrane potential). The impact of metals on chlorophyll a (Chl a) autofluorescence was also evaluated. Esterase activity was the most sensitive parameter. At the concentrations studied, all metals induced the loss of esterase activity. SG could be used to effectively detect the loss of membrane integrity in algal cells exposed to 0.32 or 1.3 μmol L−1 Cu(II). Rh123 revealed a decrease in the mitochondrial membrane potential of algal cells exposed to 0.32 and 1.3 μmol L−1 Cu(II), indicating that mitochondrial activity was compromised. Chl a autofluorescence was also affected by the presence of Cr(VI) and Cu(II), suggesting perturbation of photosynthesis. In conclusion, the fluorescence-based approach was useful for detecting the disturbance of specific cellular characteristics. Fluorescent probes are a useful diagnostic tool for the assessment of the impact of toxicants on specific targets of P. subcapitata algal cells.

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For efficient planning of waste collection routing, large municipalities may be partitioned into convenient sectors. The real case under consideration is the municipality of Monção, in Portugal. Waste collection involves more than 1600 containers over an area of 220 km2 and a population of around 20,000 inhabitants. This is mostly a rural area where the population is distributed in small villages around the 33 boroughs centres (freguesia) that constitute the municipality. In most freguesias, waste collection is usually conducted 3 times a week. However, there are situations in which the same collection is done every day. The case reveals some general and specific characteristics which are not rare, but are not widely addressed in the literature. Furthermore, new methods and models to deal with sectorization and routing are introduced, which can be extended to other applications. Sectorization and routing are tackled following a three-phase approach. The first phase, which is the main concern of the presentation, introduces a new method for sectorization inspired by Electromagnetism and Coulomb’s Law. The matter is not only about territorial division, but also the frequency of waste collection, which is a critical issue in these types of applications. Special characteristics related to the number and type of deposition points were also a motivation for this work. The second phase addresses the routing problems in each sector: new Mixed Capacitated Arc Routing with Limited Multi-Landfills models will be presented. The last phase integrates Sectoring and Routing. Computational results confirm the effectiveness of the entire novel approach.

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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

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Tese de Doutoramento em Psicologia na área de especialização de Psicologia das Organizações apresentada ao ISPA - Instituto Universitário

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This qualitative research analyzes the individual life experiences of Portuguese expatriate leaders who left their home country to work at organizations in Angola, a place that offers better job opportunities. Through interviews with those professionals and their followers, a prototype of a Portuguese expatriate leader in Angola has been developed. Even though Angola is a former Portuguese colony, it was at war for many years and so the economic situation and culture of the country are distant from what Portuguese workers are used too, which requires them to adapt and be open-minded to change.

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The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto

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Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.