962 resultados para Cognitive-emotional interactions


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We are witnessing a fundamental transformation in how Internet of Things (IoT) is having an impact on the experience users have with data-driven devices, smart appliances, and connected products. The experience of any place is commonly defined as the result of a series of user engagements with a surrounding place in order to carry out daily activities (Golledge, 2002). Knowing about users? experiences becomes vital to the process of designing a map. In the near future, a user will be able to interact directly with any IoT device placed in his surrounding place and very little is known on what kinds of interactions and experiences a map might offer (Roth, 2015). The main challenge is to develop an experience design process to devise maps capable of supporting different user experience dimensions such as cognitive, sensory-physical, affective, and social (Tussyadiah and Zach, 2012). For example, in a smart city of the future, the IoT devices allowing a multimodal interaction with a map could help tourists in the assimilation of their knowledge about points of interest (cognitive experience), their association of sounds and smells to these places (sensory-physical experience), their emotional connection to them (affective experience) and their relationships with other nearby tourists (social experience). This paper aims to describe a conceptual framework for developing a Mapping Experience Design (MXD) process for building maps for smart connected places of the future. Our MXD process is focussed on the cognitive dimension of an experience in which a person perceives a place as a "living entity" that uses and feeds through his experiences. We want to help people to undergo a meaningful experience of a place through mapping what is being communicated during their interactions with the IoT devices situated in this place. Our purpose is to understand how maps can support a person?s experience in making better decisions in real-time.

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Sin duda, el rostro humano ofrece mucha más información de la que pensamos. La cara transmite sin nuestro consentimiento señales no verbales, a partir de las interacciones faciales, que dejan al descubierto nuestro estado afectivo, actividad cognitiva, personalidad y enfermedades. Estudios recientes [OFT14, TODMS15] demuestran que muchas de nuestras decisiones sociales e interpersonales derivan de un previo análisis facial de la cara que nos permite establecer si esa persona es confiable, trabajadora, inteligente, etc. Esta interpretación, propensa a errores, deriva de la capacidad innata de los seres humanas de encontrar estas señales e interpretarlas. Esta capacidad es motivo de estudio, con un especial interés en desarrollar métodos que tengan la habilidad de calcular de manera automática estas señales o atributos asociados a la cara. Así, el interés por la estimación de atributos faciales ha crecido rápidamente en los últimos años por las diversas aplicaciones en que estos métodos pueden ser utilizados: marketing dirigido, sistemas de seguridad, interacción hombre-máquina, etc. Sin embargo, éstos están lejos de ser perfectos y robustos en cualquier dominio de problemas. La principal dificultad encontrada es causada por la alta variabilidad intra-clase debida a los cambios en la condición de la imagen: cambios de iluminación, oclusiones, expresiones faciales, edad, género, etnia, etc.; encontradas frecuentemente en imágenes adquiridas en entornos no controlados. Este de trabajo de investigación estudia técnicas de análisis de imágenes para estimar atributos faciales como el género, la edad y la postura, empleando métodos lineales y explotando las dependencias estadísticas entre estos atributos. Adicionalmente, nuestra propuesta se centrará en la construcción de estimadores que tengan una fuerte relación entre rendimiento y coste computacional. Con respecto a éste último punto, estudiamos un conjunto de estrategias para la clasificación de género y las comparamos con una propuesta basada en un clasificador Bayesiano y una adecuada extracción de características. Analizamos en profundidad el motivo de porqué las técnicas lineales no han logrado resultados competitivos hasta la fecha y mostramos cómo obtener rendimientos similares a las mejores técnicas no-lineales. Se propone un segundo algoritmo para la estimación de edad, basado en un regresor K-NN y una adecuada selección de características tal como se propuso para la clasificación de género. A partir de los experimentos desarrollados, observamos que el rendimiento de los clasificadores se reduce significativamente si los ´estos han sido entrenados y probados sobre diferentes bases de datos. Hemos encontrado que una de las causas es la existencia de dependencias entre atributos faciales que no han sido consideradas en la construcción de los clasificadores. Nuestro resultados demuestran que la variabilidad intra-clase puede ser reducida cuando se consideran las dependencias estadísticas entre los atributos faciales de el género, la edad y la pose; mejorando el rendimiento de nuestros clasificadores de atributos faciales con un coste computacional pequeño. Abstract Surely the human face provides much more information than we think. The face provides without our consent nonverbal cues from facial interactions that reveal our emotional state, cognitive activity, personality and disease. Recent studies [OFT14, TODMS15] show that many of our social and interpersonal decisions derive from a previous facial analysis that allows us to establish whether that person is trustworthy, hardworking, intelligent, etc. This error-prone interpretation derives from the innate ability of human beings to find and interpret these signals. This capability is being studied, with a special interest in developing methods that have the ability to automatically calculate these signs or attributes associated with the face. Thus, the interest in the estimation of facial attributes has grown rapidly in recent years by the various applications in which these methods can be used: targeted marketing, security systems, human-computer interaction, etc. However, these are far from being perfect and robust in any domain of problems. The main difficulty encountered is caused by the high intra-class variability due to changes in the condition of the image: lighting changes, occlusions, facial expressions, age, gender, ethnicity, etc.; often found in images acquired in uncontrolled environments. This research work studies image analysis techniques to estimate facial attributes such as gender, age and pose, using linear methods, and exploiting the statistical dependencies between these attributes. In addition, our proposal will focus on the construction of classifiers that have a good balance between performance and computational cost. We studied a set of strategies for gender classification and we compare them with a proposal based on a Bayesian classifier and a suitable feature extraction based on Linear Discriminant Analysis. We study in depth why linear techniques have failed to provide competitive results to date and show how to obtain similar performances to the best non-linear techniques. A second algorithm is proposed for estimating age, which is based on a K-NN regressor and proper selection of features such as those proposed for the classification of gender. From our experiments we note that performance estimates are significantly reduced if they have been trained and tested on different databases. We have found that one of the causes is the existence of dependencies between facial features that have not been considered in the construction of classifiers. Our results demonstrate that intra-class variability can be reduced when considering the statistical dependencies between facial attributes gender, age and pose, thus improving the performance of our classifiers with a reduced computational cost.

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Although androgens are commonly seen as male sex hormones, it has been established over the years that in both sexes, androgens also respond to social challenges. To explain the socially driven changes in androgens, two theoretical models have been proposed: the biosocial model and the challenge hypothesis. These models are typically seen as partly overlapping; however, they generate different predictions that are clarified here. In humans, sports competition and nonmetabolic competitive tasks have been used in the laboratory setting, as a proxy for agonistic interactions in animals. The results reviewed here show that the testosterone (T) response to competition in humans is highly variable – the studies present postcompetition T levels and changes in T that depend on the contest outcome and that cannot be predicted by the current theoretical models. These conflicting results bring to the foreground the importance of considering cognitive factors that could moderate the androgen response to competition. Among these variables, we elect cognitive appraisal and its components as a key candidate modulating factor. It is known that T also modulates the cognitive processes that are relevant to performance in competition. In this article, we reviewed the evidence arising from studies investigating the effect of administering exogenous T and compare those results with the findings from studies that measured endogenous T levels. Finally, we summarized the importance of also considering the interaction between androgens and other hormones, such as cortisol, when investigating the social modulation of T, as proposed by the dual-hormone hypothesis.

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Thesis (Ph.D.)--University of Washington, 2016-06

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Gray's Reinforcement Sensitivity Theory (RST) consists of the Behavioural Activation System (BAS) which is the basis of Impulsivity, and Behavioural Inhibition System (BIS) which is the basis of Anxiety. In this study, Impulsivity and Anxiety were used as distal predictors of attitudes to religion in the prediction of three religious dependent variables (Church attendance, Amount of prayer, and Importance of church). We hypothesised that Impulsivity would independently predict a Rewarding attitude to the Church and that Anxiety would independently predict an Anxious attitude to the church, and that these attitudes would be proximal predictors of our dependent variables. Moreover, we predicted that interactions between predictors would be proximal. Using structural equation modelling, data from 400 participants supported the hypotheses. We also tested Eysenck's personality scales of Extraversion and Neuroticism and found a key path of the structural equation model to be non-significant. (C) 2003 Elsevier Ltd. All rights reserved.

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One reason for the neglect of the role of positive factors in cognitive-behavioural therapy (CBT) may relate to a failure to develop cognitive models that integrate positive and negative cognitions. Bandura [Psychol. Rev. 84 (1977) 191; Anxiety Res. 1 (1988) 77] proposed that self-efficacy beliefs mediate a range of emotional and behavioural outcomes. However, in panic disorder, cognitively based research to date has largely focused on catastrophic misinterpretation of bodily sensations. Although a number of studies support each of the predictions associated with the account of panic disorder that is based on the role of negative cognitions, a review of the literature indicated that a cognitively based explanation of the disorder may be considerably strengthened by inclusion of positive cognitions that emphasize control or coping. Evidence to support an Integrated Cognitive Model (ICM) of panic disorder was examined and the theoretical implications of this model were discussed in terms of both schema change and compensatory skills accounts of change processes in CBT. (C) 2004 Elsevier Ltd. All rights reserved.

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A belief that doctors or family control one's health outcomes (external health locus of control), and a belief in one's own ability to achieve desired outcomes (general self-efficacy), may influence distress experienced in relation to a physical illness. This study examined the interaction between illness severity, external health locus of control and general self-efficacy in relation to distress. Illness severity was defined as acute or chronic illness, with the latter expected to be more stressful. Participants described a serious illness they experienced, and completed self-report scales in relation to it. Results confirmed that chronic illnesses were associated with more distress than acute illnesses across the sample. Hierarchical multiple regression analyses supported the predicted effects on distress of a three-way interaction involving external health locus of control, general self-efficacy and illness severity (acute vs. chronic). Analysis of these results may assist in explaining inconsistencies in previous research, and offer a model for understanding the role of person variables in emotional distress.

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Cued recall with an extralist cue poses a challenge for contemporary memory theory in that there is a need to explain how episodic and semantic information are combined. A parallel activation and intersection approach proposes one such means by assuming that an experimental cue will elicit its preexisting semantic network and a context cue will elicit a list memory. These 2 sources of information are then combined by focusing on information that is common to the 2 sources. Two key predictions of that approach are examined: (a) Combining semantic and episodic information can lead to item interactions and false memories, and (b) these effects are limited to memory tasks that involve an episodic context cue. Five experiments demonstrate such item interactions and false memories in cued recall but not in free association. Links are drawn between the use of context in this setting and in other settings.

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Rumor discourse has been conceptualized as an attempt to reduce anxiety and uncertainty via a process of social sensemaking. Fourteen rumors transmitted on various Internet discussion groups were observed and content analyzed over the life of each rumor With this (previously unavailable) more ecologically robust methodology, the intertwined threads of sensemaking and the gaining of interpretive control are clearly evident in the tapestry of rumor discourse. We propose a categorization of statements (the Rumor Interaction Analysis System) and find differences between dread rumors and wish rumors in anxiety-related content categories. Cluster analysis of these statements reveals a typology of voices (communicative postures) exhibiting sensemaking activities of the rumor discussion group, such as hypothesizing, skeptical critique, directing of activities to gain information, and presentation of evidence. These findings enrich our understanding of the long-implicated sensemaking function of rumor by clarifying the elements of communication that operate in rumor's social context.

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Background. The problem-gambling literature has identified a range of individual, cognitive, behavioral and emotional factors as playing important roles in the development, maintenance and treatment of problem gambling. However, familial factors have often been neglected. The current study aims to investigate the possible influence of parental factors on offspring gambling behavior. Method. A total of 189 families (546 individuals) completed several questionnaires including the South Oaks Gambling Screen (SOGS) and the Gambling Related Cognition Scale (GRCS). The relationships were examined using Pearson product-moment correlations and structural equation modeling (SEM) analyses. Results. Results showed that generally parents' (especially fathers') gambling cognitions and gambling behaviors positively correlated with offspring gambling behaviors and cognitions. However, SEM analyses showed that although parental gambling behavior was directly related to offspring gambling behavior, parental cognitions were not related to offspring gambling behavior directly but indirectly via offspring cognitions. Conclusion. The findings show that the influence of parental gambling cognition on offspring gambling behavior is indirect and via offspring cognitions. The results suggest a possible cognitive mechanism of transmission of gambling behavior in the family from one generation to the next.

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The ease with which we perform tasks such as opening the lid of a jar, in which the two hands execute quite different actions, belies the fact that there is a strong tendency for the movements of the upper limbs to be drawn systematically towards one another. Mirror movements, involuntary contractions during intended unilateral engagement of the opposite limb, are considered pathological, as they occur in association with specific disorders of the CNS. Yet they are also observed frequently in normally developing children, and motor irradiation, an increase in the excitability of the (opposite) homologous motor pathways when unimanual movements are performed, is a robust feature of the mature motor system. The systematic nature of the interactions that occur between the upper limbs has also given rise to the expectation that functional improvements in the control of a paretic limb may occur when movements are performed in a bimanual context. In spite of the ubiquitous nature of these phenomena, there is remarkably little consensus concerning the neural basis of their mediation. In the present review, consideration is given to the putative roles of uncrossed corticofugal fibers, branched bilateral corticomotoroneuronal projections, and segmental networks. The potential for bilateral interactions to occur in various brain regions including the primary motor cortex, the supplementary motor area, non-primary motor areas, the basal ganglia, and the cerebellum is also explored. This information may provide principled bases upon which to evaluate and develop task and deficit-specific programs of movement rehabilitation and therapy. (c) 2005 Elsevier B.V. All rights reserved.

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Individuals seeking compensation following traumatic brain injury (TBI) are often found to report a disproportionately high level of symptoms relative to objective indicators of impairment. Previous studies highlight that level of symptom reporting is also related to self-awareness, causal attribution, and emotional wellbeing. Therefore, the reasons for high symptom reporting in the context of compensation are generally unclear. This study aimed to identify whether self-awareness, causal attribution, and emotional wellbeing are significantly associated with level of symptom reporting after controlling for compensation status. A sample of 54 participants with TBI comprised two groups, namely, claimants (n = 27) and non-claimants (n = 27), who were similar in terms of demographic and neuro-cognitive variables. Participants completed the Symptom Expectancy Checklist, Hospital Anxiety Depression Scale, Awareness Questionnaire and a causal attribution scale. A series of independent t tests and Pearson's correlations identified that a higher level of symptom reporting was associated with the following: seeking compensation, less severe TBI, increased age, greater self-awareness, increased post-injury changes reported by relatives, a higher level of mood symptoms, and a tendency to blame other people. Multivariate analysis identified that after controlling for demographic, injury, and compensation status variables, level of mood symptoms and self-awareness were significantly associated with level of symptom reporting. The findings suggest that mood symptoms and heightened self-awareness are significantly related to high symptom reporting independent of compensation status, thus supporting the need for clinicians to interpret symptom reporting within a biopsychosocial context.