Emotional intelligence compensates for low IQ and boosts low emotionality individuals in a self-presentation task

The research on emotional intelligence (EI) has focused mainly on testing the incremental validity of EI with respect to general intelligence and personality; less attention has been devoted to investigating the potential interaction effects. In a self-presentation task that required participants to obtain positive evaluations from others, individuals low in IQ but high in EI performed as well as the high IQ individuals. In addition, the low emotionality individuals performed significantly higher when also high in EI. The results extend the previous findings on the compensatory effect of EI on low IQ to the domain of interpersonal effectiveness and shed light on the effective functioning of personality traits when interpreted with the interaction of EI. Overall this study suggests that the role of EI in predicting performance might have been overlooked by checking solely for main effects and illustrates new venues for understanding the contribution of EI in explaining emotion-laden performance.

Reducción del vector de características de reconocimiento facial

In this present work, we are proposing a characteristics reduction system for a facial biometric identification system, using transformed domains such as discrete cosine transformed (DCT) and discrete wavelets transformed (DWT) as parameterization; and Support Vector Machines (SVM) and Neural Network (NN) as classifiers. The size reduction has been done with Principal Component Analysis (PCA) and with Independent Component Analysis (ICA). This system presents a similar success results for both DWT-SVM system and DWT-PCA-SVM system, about 98%. The computational load is improved on training mode due to the decreasing of input’s size and less complexity of the classifier.

Spontaneous Speech and Emotional Response modeling based on One-class classifier oriented to Alzheimer Disease diagnosis

The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.

Lower incisor dentoalveolar compensation and symphysis dimensions among Class I and III malocclusion patients with different facial vertical skeletal patterns

Objective: To compare lower incisor dentoalveolar compensation and mandible symphysis morphology among Class I and Class III malocclusion patients with different facial vertical skeletal patterns. Materials and Methods: Lower incisor extrusion and inclination, as well as buccal (LA) and lingual (LP) cortex depth, and mandibular symphysis height (LH) were measured in 107 lateral cephalometric x-rays of adult patients without prior orthodontic treatment. In addition, malocclusion type (Class I or III) and facial vertical skeletal pattern were considered. Through a principal component analysis (PCA) related variables were reduced. Simple regression equation and multivariate analyses of variance were also used. Results: Incisor mandibular plane angle (P < .001) and extrusion (P  =  .03) values showed significant differences between the sagittal malocclusion groups. Variations in the mandibular plane have a negative correlation with LA (Class I P  =  .03 and Class III P  =  .01) and a positive correlation with LH (Class I P  =  .01 and Class III P  =  .02) in both groups. Within the Class III group, there was a negative correlation between the mandibular plane and LP (P  =  .02). PCA showed that the tendency toward a long face causes the symphysis to elongate and narrow. In Class III, alveolar narrowing is also found in normal faces. Conclusions: Vertical facial pattern is a significant factor in mandibular symphysis alveolar morphology and lower incisor positioning, both for Class I and Class III patients. Short-faced Class III patients have a widened alveolar bone. However, for long-faced and normal-faced Class III, natural compensation elongates the symphysis and influences lower incisor position.

Fischbesatz: Komplex und emotional

In fast allen Schweizer Gewässern werden von Fischern und Natur- schützern Besatzmassnahmen mit verschiedenen Fischarten durchge- führt. Es gibt allerdings viele offene Fragen, die die Forschung nur zu- sammen mit der Praxis beantworten kann.

Verbal emotional memory in a case with left amygdala damage.

The amygdala nuclei appear to be critically implicated in emotional memory. However, in most studies, encoding and consolidation processes cannot be analyzed separately. We thus studied the verbal emotional memory in a young woman with a ganglioglioma of the left amygdala and analyzed its impact (1) on each step of the memory process (encoding, retrieval, and recognition) (2) on short- and long-term consolidation (1-hour and 1-week delay) and (3) on processing of valence (positive and negative items compared to neutral words). Results showed emotional encoding impairments and, after encoding was controlled for, emotional long-term consolidation. Finally, although the negative words were not acknowledged as emotionally arousing by the patient, these words were specifically poorly encoded, recalled, and consolidated. Our data suggest that separate cerebral networks support the processing of emotional versus neutral stimuli.

La música i la multiculturalitat a l'aula. Com la pràctica de les diferents expressions musicals dels infants a l'aula pot ajudar al coneixement mutu en el grup- classe

Actualment, vivim en una societat on hi conviuen diferents cultures i la música és un llenguatge que s’utilitza en totes elles. Aquest treball tractarà el tema de la música i la multiculturalitat a l’aula per investigar si és possible, a partir de la música dels diferents països d’origen dels infants, conèixer-se millor i conèixer millor als companys. Com a mestres hem de tenir en compte totes les cultures de la nostra aula per tal d’ajudar als infants a respectar i valorar cada una d’elles. En aquesta investigació trobarem quina ha estat la metodologia d’estudi, quina ha estat la intervenció a l’aula i quins són els resultats que hem obtingut.

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

Estudio de las técnicas de reconocimiento facial en obras de arte a través de la visión por computador

El objetivo de esta investigación es comprobar la utilidad de las técnicas actuales de reconocimiento facial a través de la visión por computador en entornos museísticos. Para alcanzar este fin, he seguido las estrategias de diseño y creación para crear una aplicación que me permita posteriormente realizar una serie de experimentos, los cuales me proporcionarán los datos necesarios con los que evaluar la funcionalidad de estas técnicas existentes en obras de arte, en mi caso concretamente, sobre cuadros.

Towards a lightweight adaptative multicomponential affective recognition system

As part of the Affective Computing research field, the development of automatic affective recognition systems can enhance human-computer interactions by allowing the creation of interfaces that react to the user's emotional state. To that end, this Master Thesis brings affect recognition to nowadays most used human computer interface, mobile devices, by developing a facial expression recognition system able to perform detection under the difficult conditions of viewing angle and illumination that entails the interaction with a mobile device. Moreover, this Master Thesis proposes to combine emotional features detected from expression with contextual information of the current situation, to infer a complex and extensive emotional state of the user. Thus, a cognitive computational model of emotion is defined that provides a multicomponential affective state of the user through the integration of the detected emotional features into appraisal processes. In order to account for individual differences in the emotional experience, these processes can be adapted to the culture and personality of the user.

An fMRI Study of Emotional engagement in decicion-making

It has been suggested that decisionmaking depends on sensitive feelings associatedwith cognitive processing rather than cognitiveprocessing alone. From human lesions, we knowthe medial anterior inferior-ventral prefrontalcortex processes the sensitivity associated withcognitive processing, it being essentiallyresponsible for decision making.In this fMRI (functional Magnetic ResonanceImage) study 15 subjects were analyzed usingmoral dilemmas as probes to investigate the neuralbasis for painful-emotional sensitivity associatedwith decision making. We found that a networkcomprising the posterior and anterior cingulateand the medial anterior prefrontal cortex wassignificantly and specifically activated by painfulmoral dilemmas, but not by non-painful dilemmas.These findings provide new evidence that thecingulate and medial anterior prefrontal areinvolved in processing painful emotionalsensibility, in particular, when decision makingtakes place. We speculate that decision makinghas a cognitive component processed by cognitivebrain areas and a sensitivity component processedby emotional brain areas. The structures activatedsuggest that decision making depends on painfulemotional feeling processing rather than cognitiveprocessing when painful feeling processinghappens