Plastic deformation at high temperatures of pure and Mn-doped GaSb

In this work the plastic behavior of GaSb and Mn-doped GaSb at high temperature has been analyzed. Several experiments at different constant load and temperatures around 500 °C were carried out. The parameters used in the Haasen model have been obtained experimentally and compared with the ones obtained from simulations

Bodily sensation maps: Exploring a new direction for detecting emotions from user self-reported data

The ability of detecting emotions is essential in different fields such as user experience (UX), affective computing, and psychology. This paper explores the possibility of detecting emotions through user-generated bodily sensation maps (BSMs). The theoretical basis that inspires this work is the proposal by Nummenmaa et al. (2014) of BSMs for 14 emotions. To make it easy for users to create a BSM of how they feel, and convenient for researchers to acquire and classify users’ BSMs, we created a mobile app, called EmoPaint. The app includes an interface for BSM creation, and an automatic classifier that matches the created BSM with the BSMs for the 14 emotions. We conducted a user study aimed at evaluating both components of EmoPaint. First, it shows that the app is easy to use, and is able to classify BSMs consistently with the considered theoretical approach. Second, it shows that using EmoPaint increases accuracy of users’ emotion classification when compared with an adaptation of the well-known method of using the Affect Grid with the Circumplex Model, focused on the same set of 14 emotions of Nummenmaa et al. Overall, these results indicate that the novel approach of using BSMs in the context of automatic emotion detection is promising, and encourage further developments and studies of BSM-based methods

Endmember extraction algorithms from hyperspectral images

During the last years, several high-resolution sensors have been developed for hyperspectral remote sensing applications. Some of these sensors are already available on space-borne devices. Space-borne sensors are currently acquiring a continual stream of hyperspectral data, and new efficient unsupervised algorithms are required to analyze the great amount of data produced by these instruments. The identification of image endmembers is a crucial task in hyperspectral data exploitation. Once the individual endmembers have been identified, several methods can be used to map their spatial distribution, associations and abundances. This paper reviews the Pixel Purity Index (PPI), N-FINDR and Automatic Morphological Endmember Extraction (AMEE) algorithms developed to accomplish the task of finding appropriate image endmembers by applying them to real hyperspectral data. In order to compare the performance of these methods a metric based on the Root Mean Square Error (RMSE) between the estimated and reference abundance maps is used

Assimilating SAR-derived water level data into a hydraulic model: a case study

Satellite-based active microwave sensors not only provide synoptic overviews of flooded areas, but also offer an effective way to estimate spatially distributed river water levels. If rapidly produced and processed, these data can be used for updating hydraulic models in near real-time. The usefulness of such approaches with real event data sets provided by currently existing sensors has yet to be demonstrated. In this case study, a Particle Filter-based assimilation scheme is used to integrate ERS-2 SAR and ENVISAT ASAR-derived water level data into a one-dimensional (1-D) hydraulic model of the Alzette River. Two variants of the Particle Filter assimilation scheme are proposed with a global and local particle weighting procedure. The first option finds the best water stage line across all cross sections, while the second option finds the best solution at individual cross sections. The variant that is to be preferred depends on the level of confidence that is attributed to the observations or to the model. The results show that the Particle Filter-based assimilation of remote sensing-derived water elevation data provides a significant reduction in the uncertainty at the analysis step. Moreover, it is shown that the periodical updating of hydraulic models through the proposed assimilation scheme leads to an improvement of model predictions over several time steps. However, the performance of the assimilation depends on the skill of the hydraulic model and the quality of the observation data

A mobile application to report and detect 3D body emotional poses

Most research into automatic emotion recognition is focused on facial expressions or physiological signals, while the exploitation of body postures has scarcely been explored, although they can be useful for emotion detection. This paper first explores a mechanism for self-reporting body postures with a novel easy-to-use mobile application called EmoPose. The app detects emotional states from self-reported poses, classifying them into the six basic emotions proposed by Ekman and a neutral state. The poses identified by Schindler et al. have been used as a reference and the nearest neighbor algorithm used for the classification of poses. Finally, the accuracy in detecting emotions has been assessed by means of poses reported by a sample of users

Nonlinear Stability of Static N\'eel Walls in Ferromagnetic Thin Films

In this paper, the nonlinear (orbital) stability of static 180^\circ N\'eel walls in ferromagnetic films, under the reduced wave-type dynamics for the in-plane magnetization proposed by Capella, Melcher and Otto [CMO07], is established. It is proved that the spectrum of the linearized operator around the static N\'eel wall lies in the stable complex half plane with non-positive real part. This information is used to show that small perturbations of the static N\'eel wall converge to a translated orbit belonging to the manifold generated by the static wall.Comment: 45 page