Protest attitudes and stated preferences: Evidence on scale usage heterogeneity

We contribute to the stated preference literature by addressing scale usage heterogeneity regarding how individuals answer attitudinal questions capturing lack of trust in institutions and fairness issues. Using a latent class model, we conduct a contingent valuation study to elicit the willingness-to-pay to preserve a recreational site. We find evidence that respondents within the same class, that is, with similar preferences and attitudes, interpret the Likert scale differently when answering the attitudinal questions. We identify different patterns of scale usage heterogeneity within and across classes and associate them with individual characteristics. Our approach contributes to better a understanding of individual behavior in the presence of protest attitudes.

Human activity recognition with accelerometry: novel time and frequency features

Human Activity Recognition systems require objective and reliable methods that can be used in the daily routine and must offer consistent results according with the performed activities. These systems are under development and offer objective and personalized support for several applications such as the healthcare area. This thesis aims to create a framework for human activities recognition based on accelerometry signals. Some new features and techniques inspired in the audio recognition methodology are introduced in this work, namely Log Scale Power Bandwidth and the Markov Models application. The Forward Feature Selection was adopted as the feature selection algorithm in order to improve the clustering performances and limit the computational demands. This method selects the most suitable set of features for activities recognition in accelerometry from a 423th dimensional feature vector. Several Machine Learning algorithms were applied to the used accelerometry databases – FCHA and PAMAP databases - and these showed promising results in activities recognition. The developed algorithm set constitutes a mighty contribution for the development of reliable evaluation methods of movement disorders for diagnosis and treatment applications.