845 resultados para Learning Models


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A integração de tecnologias de informação e comunicação no contexto educacional tem sido tema de diversos congressos e simpósios ao redor do mundo e no Brasil. Neste sentido, vários estudos têm sido realizados com o objetivo de se obter metodologias que tornem efetivo o emprego das novas tecnologias no ensino. Este artigo mostra um estudo que investigou a interação entre estudantes universitários da área de ciências exatas e um ambiente de modelagem computacional qualitativo em atividades de modelagem expressiva. Os resultados obtidos mostram que os estudantes foram capazes de criar e modificar o modelo do sistema proposto a partir de suas próprias concepções.

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This paper examines the performance of Portuguese equity funds investing in the domestic and in the European Union market, using several unconditional and conditional multi-factor models. In terms of overall performance, we find that National funds are neutral performers, while European Union funds under-perform the market significantly. These results do not seem to be a consequence of management fees. Overall, our findings are supportive of the robustness of conditional multi-factor models. In fact, Portuguese equity funds seem to be relatively more exposed to smallcaps and more value-oriented. Also, they present strong evidence of time-varying betas and, in the case of the European Union funds, of time-varying alphas too. Finally, in terms of market timing, our tests suggest that mutual fund managers in our sample do not exhibit any market timing abilities. Nevertheless, we find some evidence of timevarying conditional market timing abilities but only at the individual fund level.

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Abstract. Interest in design and development of graphical user interface (GUIs) is growing in the last few years. However, correctness of GUI's code is essential to the correct execution of the overall software. Models can help in the evaluation of interactive applications by allowing designers to concentrate on its more important aspects. This paper describes our approach to reverse engineering abstract GUI models directly from the Java/Swing code.

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Color model representation allows characterizing in a quantitative manner, any defined color spectrum of visible light, i.e. with a wavelength between 400nm and 700nm. To accomplish that, each model, or color space, is associated with a function that allows mapping the spectral power distribution of the visible electromagnetic radiation, in a space defined by a set of discrete values that quantify the color components composing the model. Some color spaces are sensitive to changes in lighting conditions. Others assure the preservation of certain chromatic features, remaining immune to these changes. Therefore, it becomes necessary to identify the strengths and weaknesses of each model in order to justify the adoption of color spaces in image processing and analysis techniques. This chapter will address the topic of digital imaging, main standards and formats. Next we will set the mathematical model of the image acquisition sensor response, which enables assessment of the various color spaces, with the aim of determining their invariance to illumination changes.

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Current software development relies increasingly on non-trivial coordination logic for com- bining autonomous services often running on di erent platforms. As a rule, however, in typical non-trivial software systems, such a coordination layer is strongly weaved within the application at source code level. Therefore, its precise identi cation becomes a major methodological (and technical) problem which cannot be overestimated along any program understanding or refactoring process. Open access to source code, as granted in OSS certi cation, provides an opportunity for the devel- opment of methods and technologies to extract, from source code, the relevant coordination information. This paper is a step in this direction, combining a number of program analysis techniques to automatically recover coordination information from legacy code. Such information is then expressed as a model in Orc, a general purpose orchestration language

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Guimarães is a world heritage site (UNESCO) since December 2001, and is hosting the European Capital of Culture (ECOC) in 2012. This paper examines the profile, destination image and motivations of tourists’ visiting Guimarães before the cultural event. Based on survey responses from 276 tourists, this study found that tourists arrived to Guimarães came from the two most important cities in the northern part of Portugal (Porto and Braga). They are relatively young and well educated compared with the average tourists that visited Portugal. The results suggest that many tourists are aware of the city status as a world heritage site encompassing a historic centre, monuments, and architectural buildings. Further, these perceptions shape the image of Guimarães, as the factor analysis indicates that “historical background and functionality” is the most reliable and valid factor behind the choice of visiting the city. Finally, the main tourists’ motivation to choose Guimarães as theirs destination is educational, rather than recreational as they want to live a learning experience.

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A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

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Após uma contextualização dos jogos para crianças, enquanto ferramenta lúdico-educativa, este artigo apresenta uma abordagem para o desenvolvimento de jogos educativos utilizando redes de Petri coloridas (colored petri nets - CPN) conectadas a um servidor de aplicações 3D. No final do artigo é feita uma análise dos resultados obtidos, evidenciando a interatividade entre o utilizador e os conteúdos do jogo.

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A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

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Este artigo tem suas raízes em algumas questões relacionadas à "forma" e ao "conteúdo" do que nós, professores, ensinamos na área de Administração da Produção e Operações. Inicialmente, descrevo a evolução histórica desse campo no Brasil. Em seguida, discuto a crise de identidade que o campo está sofrendo. Com o objetivo de apresentar respostas para essa situação, apresento seis propostas para o desenvolvimento e consolidação do campo. Finalmente, descrevo uma iniciativa prática, envolvendo uma disciplina específica da área, ensinada para alunos de pós-graduação. Essa iniciativa enfatiza a "dimensão do conteúdo" (de uma abordagem técnico-operacional para uma abordagem estratégico-gerencial) como também a "dimensão da forma" (do foco no ensino para o foco no aprendizado). O sucesso dessa experiência em curso confirma a coerência da agenda proposta e induz futuros aperfeiçoamentos.

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This paper shows the results of the empirical study conducted in 186 tourist accommodation businesses in Spain certified under the "Q for Tourist Quality", own System Quality Management. It was raised with the purpose of analyzing the structure of the relationship between critical quality factors and results-social impact, how they operate and the level of their influence on obtaining these results within the company. Starting from a deep theoretical revision we propose a theoretical model together with the hypotheses to be tested, and we proceed to validation using the technique of Structural Equation Models. The results obtained show that companies wishing to improve their social impact should take into account that leadership is the most important factor to achieve it. Leadership indirectly affects the social impact through its influence on alliances and resources, quality policy/planning, personnel management and learning.

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The purpose of this study is to investigate the contribution of psychological variables and scales suggested by Economic Psychology in predicting individuals’ default. Therefore, a sample of 555 individuals completed a self-completion questionnaire, which was composed of psychological variables and scales. By adopting the methodology of the logistic regression, the following psychological and behavioral characteristics were found associated with the group of individuals in default: a) negative dimensions related to money (suffering, inequality and conflict); b) high scores on the self-efficacy scale, probably indicating a greater degree of optimism and over-confidence; c) buyers classified as compulsive; d) individuals who consider it necessary to give gifts to children and friends on special dates, even though many people consider this a luxury; e) problems of self-control identified by individuals who drink an average of more than four glasses of alcoholic beverage a day.

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The ability to foresee how behaviour of a system arises from the interaction of its components over time - i.e. its dynamic complexity – is seen an important ability to take effective decisions in our turbulent world. Dynamic complexity emerges frequently from interrelated simple structures, such as stocks and flows, feedbacks and delays (Forrester, 1961). Common sense assumes an intuitive understanding of their dynamic behaviour. However, recent researches have pointed to a persistent and systematic error in people understanding of those building blocks of complex systems. This paper describes an empirical study concerning the native ability to understand systems thinking concepts. Two different groups - one, academic, the other, professional – submitted to four tasks, proposed by Sweeney and Sterman (2000) and Sterman (2002). The results confirm a poor intuitive understanding of the basic systems concepts, even when subjects have background in mathematics and sciences.

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This study develops a theoretical model that explains the effectiveness of the balanced scorecard approach by means of a system dynamics and feedback learning perspective. Presumably, the balanced scorecard leads to a better understanding of context, allowing managers to externalize and improve their mental models. We present a set of hypotheses about the influence of the balanced scorecard approach on mental models and performance. A test based on a simulation experiment that uses a system dynamics model is performed. The experiment included three types of parameters: financial indicators; balanced scorecard indicators; and balanced scorecard indicators with the aid of a strategy map review. Two out of the three hypotheses were confirmed. It was concluded that a strategy map review positively influences mental model similarity, and mental model similarity positively influences performance.