Towards Emotional Interaction: Using Movies to Automatically Learn Users' Emotional States

The HCI community is actively seeking novel methodologies to gain insight into the user’s experience during interaction with both the application and the content. We propose an emotional recognition engine capable of automatically recognizing a set of human emotional states using psychophysiological measures of the autonomous nervous system, including galvanic skin response, respiration, and heart rate. A novel pattern recognition system, based on discriminant analysis and support vector machine classifiers is trained using movies’ scenes selected to induce emotions ranging from the positive to the negative valence dimension, including happiness, anger, disgust, sadness, and fear. In this paper we introduce an emotion recognition system and evaluate its accuracy by presenting the results of an experiment conducted with three physiologic sensors.

DESENVOLVIMENTO DE UM CLASSIFICADOR PARA ANÁLISE BIOMÉTRICA DE UM COLETE INSTRUMENTADO PARA REEDUCAÇÃO POSTURAL

Ao longo dos tempos tem existido um avanço, nas empresas, dirigido à preocupação com o bemestar dos trabalhadores, adotando por isso medidas preventivas. A formação especializada em Medicina do Trabalho é indispensável para o exercício de atividades de prevenção dos riscos profissionais e de promoção da saúde. A postura corporal pode ser definida como a posição e a orientação global do corpo e membros relativamente uns aos outros. Qualquer desvio na forma da coluna vertebral pode gerar solicitações funcionais prejudiciais que ocasionam um aumento de fadiga no trabalhador e leva ao longo do tempo a lesões graves. Cada vez mais surgem doenças profissionais provocadas pela adoção de más posturas, na realização de tarefas diárias dos trabalhadores. A boa postura corporal é uma tarefa específica que representa uma interação complexa entre a função biomecânica e neuromuscular. No presente plano de dissertação foram estudados diferentes classificadores tendo como objetivo classificar boas e más posturas corporais de trabalhadores em contexto de trabalho. Assim foram estudados diferentes classificadores de machine learnig, redes neuronais artificiais, support vector machine, árvores de decisão, análise discriminante, regressão logística, treebagger e naíve bayes. Para treino de classificadores foi realizada a aquisição tridimensional da postura da espinha a 100 pessoas, passando por uma parametrização e treino de diferentes classificadores para a determinação automática do tipo de postura corporal. O classificador que obteve melhor desempenho foi o Treebagger com uma classificação para True Positive de 93,3% e True Negative de 96,2%.

Blood type classification using computer vision and machine learning

In emergency situations, where time for blood transfusion is reduced, the O negative blood type (the universal donor) is administrated. However, sometimes even the universal donor can cause transfusion reactions that can be fatal to the patient. As commercial systems do not allow fast results and are not suitable for emergency situations, this paper presents the steps considered for the development and validation of a prototype, able to determine blood type compatibilities, even in emergency situations. Thus it is possible, using the developed system, to administer a compatible blood type, since the first blood unit transfused. In order to increase the system’s reliability, this prototype uses different approaches to classify blood types, the first of which is based on Decision Trees and the second one based on support vector machines. The features used to evaluate these classifiers are the standard deviation values, histogram, Histogram of Oriented Gradients and fast Fourier transform, computed on different regions of interest. The main characteristics of the presented prototype are small size, lightweight, easy transportation, ease of use, fast results, high reliability and low cost. These features are perfectly suited for emergency scenarios, where the prototype is expected to be used.

Fatores determinantes da política de distribuição de dividendos: Evidência empírica para as empresas não financeiras da Euronext Lisbon

Dividends and their distribution decisions, being a component of the compensation of investors are a constant financial worry within companies, thus revealing one of the themes highlighted in the context of the financial literature. Study will address the factors determining the dividend policy practiced by companies listed in the Portuguese stock market. The latter will be 47 non-financial companies listed on the Euronext Lisbon during 2009 until 2011. The two samples that have been investigated include the representative of the majority of non-financial companies listed on Euronext Lisbon and the other financial companies members of the PSI 20. The methodology adopted is one of the ordinary least squares regression and the amount of dividends per share distributed was used in determining the dependent variable. In relation to the independent variables, six explanatory factors were chosen. These include profitability, stability of dividend policy, size, growth, risk and investment opportunities. The conclusion suggests that the most important factors to explain the amount of dividends distributed are profitability and stability of dividend policy. There after, growth and risk factors, as well as factors that explain the amount of dividends distributed are also relevant. The remaining variables obtained were insufficient evidence pointing to a significant effect in explaining the dividend policy of Portuguese companies in the sample. The conclusion also states that differences exist in the importance of the explanatory factors to the amount of dividends distributed between the study samples, given the differentiation of dividend policies, followed by companies from each group analyzed.

Desempenho empresarial e o valor da empresa no mercado de capitais: evidência empírica para o mercado de capitais português

The main objective of this paper is to analyse the effect of firms’ performance indicators in explaining the price of stocks in the Portuguese capital market, using a fundamental analysis. In the empirical setting, firms’ performance indicators are gathered into two groups: (1) economic and financial indicators and (2) stock market indicators. Using a sample of 38 firms quoted at Euronext Lisbon, estimates are obtained trough an Ordinary Least Squares (OLS) model and report to December, 31 2007. Results suggest that performance indicators are able to explain the firms’ stock market price. There is a significant positive impact of sales growth and of payout ratio, while we find a statistically significant negative effect of the firm’s financial autonomy on the stock market price for the majority of firms quoted at Euronext Lisbon.