Abstract: In this work we evaluate the possibility of predicting
the emotional state of a person based on the EEG. We investigate
the problem of classifying valence from EEG signals during
the presentation of affective pictures, utilizing the "frontal EEG
asymmetry" phenomenon. To distinguish positive and negative
emotions, we applied the Common Spatial Patterns algorithm.
In contrast to our expectations, the affective pictures did not
reliably elicit changes in frontal asymmetry. The classifying task
thereby becomes very hard as reflected by the poor classifier
performance. We suspect that the masking of the source of the
brain activity related to emotions, coming mostly from deeper
structures in the brain, and the insufficient emotional engagement
are among main reasons why it is difficult to predict the emotional
state of a person.
Abstract: The aim of this paper is description of the notion of
the death for prisoners and the ways of deal with. They express
indifference, coldness, inability to accept the blame, they have no
shame and no empathy. Is it enough to perform acts verging on the
death. In this paper we described mechanisms and regularities of selfdestructive
behaviour in the view of the relevant literature? The
explanation of the phenomenon is of a biological and sociopsychological
nature. It must be clearly stated that all forms of selfdestructive
behaviour result from various impulses, conflicts and
deficits. That is why they should be treated differently in terms of
motivation and functions which they perform in a given group of
people. Behind self-destruction there seems to be a motivational
mechanism which forces prisoners to rebel and fight against the hated
law and penitentiary systems. The imprisoned believe that pain and
suffering inflicted on them by themselves are better than passive
acceptance of repression. The variety of self-destruction acts is wide,
and some of them take strange forms. We assume that a life-death
barrier is a kind of game for them. If they cannot change the
degrading situation, their life loses sense.
Abstract: The aim of this study is to describe the associations
between the temperamental traits and the narrative emotional
expression. The Temperament Questionnaire was used: The FCB-TI
of Zawadzki & Strelau. A sample of 85 persons described three
emotional situations: love. hate, and anxiety. This study analyzes the
verbal form of expression by means of a written account of
emotions. The relationship between the narratives of love, hate and
anxiety and temperament characteristics were studied. Results
indicate that vigorousness (VI), perseverance (PE), sensory
sensitivity (SS), emotional reactivity (ER), endurance (EN) and
activeness (AC) have a significant impact on the emotional
expression in narratives. The temperamental traits are linked to the
form of emotional language. It means that temperament has an
impact on cognitive representations of emotions.
Abstract: To improve the classification rate of the face
recognition, features combination and a novel non-linear kernel are
proposed. The feature vector concatenates three different radius of
local binary patterns and Gabor wavelet features. Gabor features are
the mean, standard deviation and the skew of each scaling and
orientation parameter. The aim of the new kernel is to incorporate
the power of the kernel methods with the optimal balance between
the features. To verify the effectiveness of the proposed method,
numerous methods are tested by using four datasets, which are
consisting of various emotions, orientations, configuration,
expressions and lighting conditions. Empirical results show the
superiority of the proposed technique when compared to other
methods.
Abstract: Facial expression analysis is rapidly becoming an
area of intense interest in computer science and human-computer
interaction design communities. The most expressive way humans
display emotions is through facial expressions. In this paper we
present a method to analyze facial expression from images by
applying Gabor wavelet transform (GWT) and Discrete Cosine
Transform (DCT) on face images. Radial Basis Function (RBF)
Network is used to classify the facial expressions. As a second stage,
the images are preprocessed to enhance the edge details and non
uniform down sampling is done to reduce the computational
complexity and processing time. Our method reliably works even
with faces, which carry heavy expressions.
Abstract: Recent theorizations on the cognitive process of moral
judgment have focused on the role of intuitions and emotions, marking
a departure from previous emphasis on conscious, step-by-step
reasoning. My study investigated how being in a disgusted mood state
affects moral judgment.
Participants were induced to enter a disgusted mood state through
listening to disgusting sounds and reading disgusting descriptions.
Results shows that they, when compared to control who have not been
induced to feel disgust, are more likely to endorse actions that are
emotionally aversive but maximizes utilitarian return
The result is analyzed using the 'emotion-as-information' approach
to decision making. The result is consistent with the view that
emotions play an important role in determining moral judgment.