Persistence on airline accidents

This paper analyses airline accidents data from 1927-2006. The fractional integration methodology is adopted. It is shown that airline accidents are persistent and (fractionally) cointegrated with airline traffic. Thus, there exists an equilibrium relation between air accidents and airline traffic, with the effect of the shocks to that relationship disappearing in the long run. Policy implications are derived for countering accidents events.

Local dynamics in high-order harmonic generation using Bohmian trajectories

We investigate high-order harmonic generation from a Bohmian-mechanical perspective, and find that the innermost part of the core, represented by a single Bohmian trajectory, leads to the main contributions to the high-harmonic spectra. Using time-frequency analysis, we associate this central Bohmian trajectory to an ensemble of unbound classical trajectories leaving and returning to the core, in agreement with the three step model. In the Bohmian scenario, this physical picture builds up non-locally near the core via the quantum mechanical phase of the wavefunction. This implies that the flow of the wavefunction far from the core alters the central Bohmian trajectory. We also show how this phase degrades in time for the peripheral Bohmian trajectories as they leave the core region.Comment: 7 pages, 3 figures; the manuscript has been considerably extended and modified with regard to the previous version

Towards the development of affective facial expression recognition for human-robot interaction

Affective facial expression is a key feature of non-verbal behavior and is considered as a symptom of an internal emotional state. Emotion recognition plays an important role in social communication: human-human and also for human-robot interaction. This work aims at the development of a framework able to recognise human emotions through facial expression for human-robot interaction. Simple features based on facial landmarks distances and angles are extracted to feed a dynamic probabilistic classification framework. The public online dataset Karolinska Directed Emotional Faces (KDEF) [12] is used to learn seven different emotions (e.g. Angry, fearful, disgusted, happy, sad, surprised, and neutral) performed by seventy subjects. Offline and on-the-fly tests were carried out: leave-one-out cross validation tests using the dataset and on-the-fly tests during human-robot interactions. Preliminary results show that the proposed framework can correctly recognise human facial expressions with potential to be used in human-robot interaction scenarios

Human Activity Recognition using Max-Min Skeleton-based Features and Key Poses

Human activity recognition is still a very challenging research area, due to the inherently complex temporal and spatial patterns that characterize most human activities. This paper proposes a human activity recognition framework based on random forests, where each activity is classified requiring few training examples (i.e. no frame-by-frame activity classification). In a first approach, a simple mechanism that divides each action sequence into a fixed-size window is employed, where max-min skeleton-based features are extracted. In the second approach, each window is delimited by a pair of automatically detected key poses, where static and max-min dynamic features are extracted, based on the determined activity example. Both approaches are evaluated using the Cornell Activity Dataset [1], obtaining relevant overall average results, considering that these approaches are fast to train and require just a few training examples. These characteristics suggest that the proposed framework can beuseful for real-time applications, where the activities are typicallywell distinctive and little training time is required, or to be integrated in larger and sophisticated systems, for a first quick impression/learning of certain activitie

The epidemiology of Bean golden mosaic virus in two transgenic bean lines.

The present study was conducted to evaluate the epidemics of golden mosaic under field conditions during two seasons in 2007 and 2008

The effect of temperature on the dynamics of a homogeneous oscillatory system operated in batch and under flow

The effect of temperature on a network of chemical reactions is not obvious, especially when compared to the effect exerted on elementary steps. There are few reports regarding the estimation of parameters such as activation energies for oscillating chemical systems. Still less investigated is the importance of the relative distance from thermodynamic equilibrium on the way in which temperature influences the oscillators' dynamics – a crucial aspect for the understanding of chemical and bio-chemical oscillating networks. In this paper we use the bromate–oxalic acid–acetone–cerium oscillatory system to study the influence of temperature under close and far-from-equilibrium regimes. The research was carried out under identical conditions for batch and flow (in a continuous flow stirred tank reactor, CSTR) regimes, and the main oscillation features were preserved, so that it was possible to isolate the effect of flow. Overall, increasing the flow results in an increase of the oscillatory frequency. The apparent oscillatory activation energy was found to decrease from 72 ± 6 kJ mol−1, for the system operated in batch, to 50 ± 2 kJ mol−1, under the flow regime. The role of the distance from the thermodynamic equilibrium on the temperature dependence is generalized and discussed in connection with other systems. Numerical simulations using the Brusselator model under batch and flow regimes further helped the discussion of the main experimental results