Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.

Investigations on relational control of time perception

Tese de Doutoramento em Psicologia Básica

Atividades de campo no ensino da Geologia: opiniões de professores portugueses sobre formas ideais de as usar

Devido à elevada dimensão espacial e temporal da maior parte dos fenómenos geológicos, não é possível reproduzir no laboratório os fenómenos a estudar, pelo que, se o professor de Geologia pretender colocar os alunos em contato com esses fenómenos, terá que organizar uma saída de campo para que as necessárias e adequadas atividades sejam realizadas no lugar onde esses fenómenos ocorrem. Contudo, e apesar de professores e alunos reconhecerem diversas potencialidades didáticas das saídas de campo, os professores raramente as organizam e justificam isso com base em diversos impedimentos. Neste artigo relatam-se os resultados de um estudo em que 233 professores portugueses de Biologia e Geologia foram inquiridos acerca de formas ideais de integrar as atividades de campo na componente de Geologia, no 3º ciclo do Ensino Básico (n=102) e no Ensino Secundário (n=131). Os resultados sugerem que as práticas que os professores gostariam de implementar, caso não houvesse constrangimentos à realização de atividades de campo, não seriam, na maior parte dos casos, muito diferentes das práticas implementadas que são relatadas na literatura. Esta falta de exigência e de ousadia por parte dos professores, no que concerne ao modo como as atividades de campo deveriam ser utilizadas, sugere a necessidade de a formação inicial e contínua de professores contemplar uma abordagem adequada das saídas de campo e de as escolas se reorganizarem para facilitarem a organização, fundamentada, das mesmas.

Stress During ACLS Courses: Is it Important for Learning Skills?

OBJECTIVE: To determine the influence of stress on teaching medical emergencies in an Advanced Cardiac Life Support (ACLS) course and to verify this influence on learning, and the efficiency of emergency care training. METHODS: Seventeen physicians signed up for an ACLS course. Their pulses were taken and blood pressure (BP) verified on the first day, before the beginning of the course, and on the second day, during the theoretical and practical test (TPT). Variations in pulse rates and BP were compared with students' test grades. Then, students answered a questionnaire of variables (QV) about the amount of sleep they had during the course, the quantity of study material and the time spent studying for the course, and a stress scale graphic. RESULTS: Seven students had a pulse variation less than 10% between the 2 periods and 10 had a 10% or more variation. Grades on TPT were, respectively, 91.4±2.4 and 87.3±5.2 (p<0.05). Six students had a BP variation less than 20 mmHg, and in 11 it varied more than 21 mmHg. Grades on the TPT were 92.3±3.3 and 86.2± 8.1, respectively (p<0.05). The QV dates did not significantly influence grades. CONCLUSION: Stress, as an isolated variable, had a negative influence on the learning process and on the efficiency of emergency training in this situation.

The Word Brain - A Short Guide to Fast Language Learning

How long does it take to learn another language? How many words do you need to learn? Are languages within the reach of everybody? Which teachers would you choose and which teachers should you avoid? These are some of the questions you ask yourself when you start learning a new language.The Word Brain provides the answers. If you have learned foreign languages in the past, consider reading it. If you or your children need to learn languages in the future, you must read it. What you will discover in two hours will change for ever the way you see languages and language learning. The principles of The Word Brain are timeless. Our children’s grandchildren will follow them when they discover the people of our planet.

Learning the ropes and embracing the rules: CFSP institutions as arenas for learning and strategic socialisation

The aim of this article is to analyse those situations in which learning and socialisation take place within the context of the Common Foreign and Security Policy (CFSP), in particular, at the level of experts in the Council Working Groups. Learning can explain the institutional development of CFSP and changes in the foreign policies of the Member States. Some scope conditions for learning and channels of institutionalisation are identified. Socialisation, resulting from learning within a group, is perceived as a strategic action by reflective actors. National diplomats, once they arrive in Brussels, learn the new code of conduct of their Working Groups. They are embedded in two environments and faced with two logics: the European one in the Council and the national one in the Ministries of Foreign Affairs (MFA). The empirical evidence supports the argument that neither rational nor sociological approaches alone can account for these processes.

Stock market volatility and learning

Introducing bounded rationality in a standard consumption-based asset pricing model with time separable preferences strongly improves empirical performance. Learning causes momentum and mean reversion of returns and thereby excess volatility, persistence of price-dividend ratios, long-horizon return predictability and a risk premium, as in the habit model of Campbell and Cochrane (1999), but for lower risk aversion. This is obtained, even though our learning scheme introduces just one free parameter and we only consider learning schemes that imply small deviations from full rationality. The findings are robust to the learning rule used and other model features. What is key is that agents forecast future stock prices using past information on prices.

Using active learning for monitoring networks design: The example of wind power plants sites evaluation

Locating new wind farms is of crucial importance for energy policies of the next decade. To select the new location, an accurate picture of the wind fields is necessary. However, characterizing wind fields is a difficult task, since the phenomenon is highly nonlinear and related to complex topographical features. In this paper, we propose both a nonparametric model to estimate wind speed at different time instants and a procedure to discover underrepresented topographic conditions, where new measuring stations could be added. Compared to space filling techniques, this last approach privileges optimization of the output space, thus locating new potential measuring sites through the uncertainty of the model itself.

Testing the TASP: An Experimental Investigation of Learning in Games with Unstable Equilibria

We report experiments designed to test between Nash equilibria that are stable and unstable under learning. The “TASP” (Time Average of the Shapley Polygon) gives a precise prediction about what happens when there is divergence from equilibrium under fictitious play like learning processes. We use two 4 x 4 games each with a unique mixed Nash equilibrium; one is stable and one is unstable under learning. Both games are versions of Rock-Paper-Scissors with the addition of a fourth strategy, Dumb. Nash equilibrium places a weight of 1/2 on Dumb in both games, but the TASP places no weight on Dumb when the equilibrium is unstable. We also vary the level of monetary payoffs with higher payoffs predicted to increase instability. We find that the high payoff unstable treatment differs from the others. Frequency of Dumb is lower and play is further from Nash than in the other treatments. That is, we find support for the comparative statics prediction of learning theory, although the frequency of Dumb is substantially greater than zero in the unstable treatments.

Learning about Risk and Return: A Simple Model of Bubbles and Crashes

This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock’s return. Recursive updating of both the conditional variance and the expected return implies several mechanisms through which learning impacts stock prices. Extended periods of excess volatility, bubbles and crashes arise with a frequency that depends on the extent to which past data is discounted. A central role is played by changes over time in agents’ estimates of risk.

Time-consistent fiscal policy under heterogeneity: Conflicting or common interests?

This paper studies the aggregate and distributional implications of Markov-perfect tax-spending policy in a neoclassical growth model with capitalists and workers. Focusing on the long run, our main fi ndings are: (i) it is optimal for a benevolent government, which cares equally about its citizens, to tax capital heavily and to subsidise labour; (ii) a Pareto improving means to reduce ine¢ ciently high capital taxation under discretion is for the government to place greater weight on the welfare of capitalists; (iii) capitalists and workers preferences, regarding the optimal amount of "capitalist bias", are not aligned implying a conflict of interests.

Baysian Model Averaging, Learning and Model Selection

Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecasting model is selected in the long-run. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth's model of price determination.

Unilateral Emissions Mitigation, Spillovers, and Global Learning

What's the role of unilateral measures in global climate change mitigation in a post-Durban, post 2012 global policy regime? We argue that under conditions of preference heterogeneity, unilateral emissions mitigation at a subnational level may exist even when a nation is unwilling to commit to emission cuts. As the fraction of individuals unilaterally cutting emissions in a global strongly connected network of countries evolves over time, learning the costs of cutting emissions can result in the adoption of such activities globally and we establish that this will indeed happen under certain assumptions. We analyze the features of a policy proposal that could accelerate convergence to a low carbon world in the presence of global learning.

A first attempt of geographically-distributed Multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM): mapping human time and energy throughput in metropolitan Barcelona

This study presents a first attempt to extend the “Multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM)” approach to a spatial dimension using GIS techniques in the Metropolitan area of Barcelona. We use a combination of census and commercial databases along with a detailed land cover map to create a layer of Common Geographic Units that we populate with the local values of human time spent in different activities according to MuSIASEM hierarchical typology. In this way, we mapped the hours of available human time, in regards to the working hours spent in different locations, putting in evidence the gradients in spatial density between the residential location of workers (generating the work supply) and the places where the working hours are actually taking place. We found a strong three-modal pattern of clumps of areas with different combinations of values of time spent on household activities and on paid work. We also measured and mapped spatial segregation between these two activities and put forward the conjecture that this segregation increases with higher energy throughput, as the size of the functional units must be able to cope with the flow of exosomatic energy. Finally, we discuss the effectiveness of the approach by comparing our geographic representation of exosomatic throughput to the one issued from conventional methods.