9,041 research outputs found

    Sex differences in emotional evaluation of film clips: interaction with five high arousal emotional categories

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    The present study aimed to investigate gender differences in the emotional evaluation of 18 film clips divided into six categories: Erotic, Scenery, Neutral, Sadness, Compassion, and Fear. 41 female and 40 male students rated all clips for valence-pleasantness, arousal, level of elicited distress, anxiety, jittery feelings, excitation, and embarrassment. Analysis of positive films revealed higher levels of arousal, pleasantness, and excitation to the Scenery clips in both genders, but lower pleasantness and greater embarrassment in women compared to men to Erotic clips. Concerning unpleasant stimuli, unlike men, women reported more unpleasantness to the Compassion, Sadness, and Fear compared to the Neutral clips and rated them also as more arousing than did men. They further differentiated the films by perceiving greater arousal to Fear than to Compassion clips. Women rated the Sadness and Fear clips with greater Distress and Jittery feelings than men did. Correlation analysis between arousal and the other emotional scales revealed that, although men looked less aroused than women to all unpleasant clips, they also showed a larger variance in their emotional responses as indicated by the high number of correlations and their relatively greater extent, an outcome pointing to a masked larger sensitivity of part of male sample to emotional clips. We propose a new perspective in which gender difference in emotional responses can be better evidenced by means of film clips selected and clustered in more homogeneous categories, controlled for arousal levels, as well as evaluated through a number of emotion focused adjectives

    Positive/Negative Emotion Detection from RGB-D upper Body Images

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    International audienceThe ability to identify users'mental states represents a valu-able asset for improving human-computer interaction. Considering that spontaneous emotions are conveyed mostly through facial expressions and the upper Body movements, we propose to use these modalities together for the purpose of negative/positive emotion classification. A method that allows the recognition of mental states from videos is pro-posed. Based on a dataset composed with RGB-D movies a set of indic-tors of positive and negative is extracted from 2D (RGB) information. In addition, a geometric framework to model the depth flows and capture human body dynamics from depth data is proposed. Due to temporal changes in pixel and depth intensity which characterize spontaneous emo-tions dataset, the depth features are used to define the relation between changes in upper body movements and the affect. We describe a space of depth and texture information to detect the mood of people using upper body postures and their evolution across time. The experimentation has been performed on Cam3D dataset and has showed promising results

    Change blindness: eradication of gestalt strategies

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    Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

    Differential Impact of Interference on Internally- and Externally-Directed Attention.

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    Attention can be oriented externally to the environment or internally to the mind, and can be derailed by interference from irrelevant information originating from either external or internal sources. However, few studies have explored the nature and underlying mechanisms of the interaction between different attentional orientations and different sources of interference. We investigated how externally- and internally-directed attention was impacted by external distraction, how this modulated internal distraction, and whether these interactions were affected by healthy aging. Healthy younger and older adults performed both an externally-oriented visual detection task and an internally-oriented mental rotation task, performed with and without auditory sound delivered through headphones. We found that the addition of auditory sound induced a significant decrease in task performance in both younger and older adults on the visual discrimination task, and this was accompanied by a shift in the type of distractions reported (from internal to external). On the internally-oriented task, auditory sound only affected performance in older adults. These results suggest that the impact of external distractions differentially impacts performance on tasks with internal, as opposed to external, attentional orientations. Further, internal distractibility is affected by the presence of external sound and increased suppression of internal distraction

    Fechner Day 2022. Proceedings of the 38th Annual Meeting of the International Society for Psychophysics.

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    Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations

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    Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions

    Consultancy companies analysis: Leadership success

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    In this project, a documentation phase is carried out so as to find out the positioning of leadership in a consultancy company. Once this positioning is analyzed, hypotheses are established and they can be contrasted. With the results, conclusions will be made where future actions will be explained so as to obtain the successful leader the company desires. The process carried out in this project is done in different parts. First of all, a bibliographic revision has been made so as to obtain all the information necessary to accomplish this project. When all the information is gathered, an inquiry has been made, as a measuring instrument, to the company workers. With this tool we can see which is the best leadership definition so as to analyze the leadership situation in the consultancy company. Having all this done, a conclusion is made where the best behavior is exposed

    Analysis of Affective State as Covariate in Human Gait Identification

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    There is an increased interest in the need for a noninvasive and nonintrusive biometric identification and recognition system such as Automatic Gait Identification (AGI) due to the rise in crime rates in the US, physical assaults, and global terrorism in public places. AGI, a biometric system based on human gait, can recognize people from a distance and current literature shows that AGI has a 95.75% success rate in a closely controlled laboratory environment. Also, this success rate does not take into consideration the effect of covariate factors such as affective state (mood state); and literature shows that there is a lack of understanding of the effect of affective state on gait biometrics. The purpose of this study was to determine the percent success rate of AGI in an uncontrolled outdoor environment with affective state as the main variable. Affective state was measured using the Profile of Mood State (POMS) scales. Other covariate factors such as footwear or clothes were not considered in this study. The theoretical framework that grounded this study was Murray\u27s theory of total walking cycle. This study included the gait signature of 24 participants from a population of 62 individuals, sampled based on simple random sampling. This quantitative research used empirical methods and a Fourier Series Analysis. Results showed that AGI has a 75% percent success rate in an uncontrolled outdoor environment with affective state. This study contributes to social change by enhancing an understanding of the effect of affective state on gait biometrics for positive identification during and after a crime such as bank robbery when the use of facial identification from a surveillance camera is either not clear or not possible. This may also be used in other countries to detect suicide bombers from a distance
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