898 resultados para HUMAN BEHAVIOR


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The World Trade Center Evacuation: The evacuation of the WTC complex represents one of the largest full-scale evacuations of people in modern times.

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Die Dissertation besteht im Wesentlichen aus zwei Teilen: der Synopse und einem empirischen Teil. In der Synopse werden die Befunde aus dem empirischen Teil zusammengefasst und mit der bisherigen Forschungsliteratur in Zusammenhang gesetzt. Im empirischen Teil werden alle Studien, die für diese Dissertation durchgeführt wurden, in Paper-Format berichtet. Im ersten Teil der Synopse werden grundlegende Annahmen der Terror Management Theorie (TMT) dargelegt—mit besonderem Schwerpunkt auf die Mortalitätssalienz (MS)-Hypothese, die besagt, dass die Konfrontation mit der eigenen Sterblichkeit die Motivation erhöht das eigene Weltbild zu verteidigen und nach Selbstwert zu streben. In diesem Kontext wird auch die zentrale Rolle von Gruppen erklärt. Basierend auf diesen beiden Reaktionen, wird TMT Literatur angeführt, die sich auf bestimmte kulturelle Werte und soziale Normen bezieht (wie prosoziale und pro-Umwelt Normen, materialistische und religiöse Werte, dem Wert der Ehrlichkeit, die Norm der Reziprozität und deskriptive Normen). Darüber hinaus werden Randbedingungen, wie Gruppenmitgliedschaft und Norm-Salienz, diskutiert. Zuletzt folgt eine Diskussion über die Rolle von Gruppen, der Funktion des Selbstwerts und über Perspektiven einer friedlichen Koexistenz. Der empirische Teil enthält elf Studien, die in acht Papern berichtet werden. Das erste Paper behandelt die Rolle von Gruppenmitgliedschaft unter MS, wenn es um die Bewertung von anderen geht. Das zweite Manuskript geht der Idee nach, dass Dominanz über andere für Sadisten eine mögliche Quelle für Selbstwert ist und daher unter MS verstärkt ausgeübt wird. Das dritte Paper untersucht prosoziales Verhalten in einer Face-to-Face Interaktion. Im vierten Paper wird gezeigt, dass Personen (z.B. Edward Snowden), die im Namen der Wahrheit handeln, unter MS positiver bewertet werden. Im fünften Paper zeigen zwei Studien, dass MS dazu führt, dass mögliche gelogene Aussagen kritischer beurteilt werden. Das sechste Paper zeigt, dass der Norm der Reziprozität unter MS stärker zugestimmt wird. Das siebte Paper geht der Frage nach, inwiefern MS das Einhalten dieser Norm beeinflusst. Und schließlich wird im achten Paper gezeigt, dass MS die Effektivität der Door-in-the-Face Technik erhöht—eine Technik, die auf der Norm der Reziprozität basiert.

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The ability to learn and recognize human activities of daily living (ADLs) is important in building pervasive and smart environments. In this paper, we tackle this problem using the hidden semi-Markov model. We discuss the state-of-the-art duration modeling choices and then address a large class of exponential family distributions to model state durations. Inference and learning are efficiently addressed by providing a graphical representation for the model in terms of a dynamic Bayesian network (DBN). We investigate both discrete and continuous distributions from the exponential family (Poisson and Inverse Gaussian respectively) for the problem of learning and recognizing ADLs. A full comparison between the exponential family duration models and other existing models including the traditional multinomial and the new Coxian are also presented. Our work thus completes a thorough investigation into the aspect of duration modeling and its application to human activities recognition in a real-world smart home surveillance scenario.

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Human behavior is a major factor modulating the consequences of road tunnel accidents. We investigated the effect of information and instruction on drivers' behavior as well as the usability of virtual environments to simulate such emergency situations. Tunnel safety knowledge of the general population was assessed using an online questionnaire, and tunnel safety behavior was investigated in a virtual reality experiment. Forty-four participants completed three drives through a virtual road tunnel and were confronted with a traffic jam, no event, and an accident blocking the road. Participants were randomly assigned to a control group (no intervention), an informed group who read a brochure containing safety information prior to the tunnel drives, or an informed and instructed group who read the same brochure and received additional instructions during the emergency situation. Informed participants showed better and quicker safety behavior than the control group. Self-reports of anxiety were assessed three times during each drive. Anxiety was elevated during and after the emergency situation. The findings demonstrate problematic safety behavior in the control group and that knowledge of safety information fosters adequate behavior in tunnel emergencies. Enhanced anxiety ratings during the emergency situation indicate external validity of the virtual environment.

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In this book, an international group of leading scientists present perspectives on the control of human behavior, awareness, consciousness, and the meaning and function of perceived control or self-efficacy in people's lives. The book breaks down the barriers between subdisciplines, and thus constitutes an occasion to reflect on various facets of control in human life. Each expert reviews his or her field through the lens of perceived control and shows how these insights can be applied in practice.

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An evolutionary model of human behavior should privilege emotions: essential, phylogenetically ancient behaviors that learning and decision making only subserve. Infants and non-mammals lack advanced cognitive powers but still survive. Decision making is only a means to emotional ends, which organize and prioritize behavior. The emotion of pride/shame, or dominance striving, bridges the social and biological sciences via internalization of cultural norms.

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For many years, humans and machines have shared the same physical space. To facilitate their interaction with humans, their social integration and for more rational behavior has been sought that the robots demonstrate human-like behavior. For this it is necessary to understand how human behavior is generated, discuss what tasks are performed and how relate to themselves, for subsequent implementation in robots. In this paper, we propose a model of competencies based on human neuroregulator system for analysis and decomposition of behavior into functional modules. Using this model allow separate and locate the tasks to be implemented in a robot that displays human-like behavior. As an example, we show the application of model to the autonomous movement behavior on unfamiliar environments and its implementation in various simulated and real robots with different physical configurations and physical devices of different nature. The main result of this work has been to build a model of competencies that is being used to build robotic systems capable of displaying behaviors similar to humans and consider the specific characteristics of robots.

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Humans and machines have shared the same physical space for many years. To share the same space, we want the robots to behave like human beings. This will facilitate their social integration, their interaction with humans and create an intelligent behavior. To achieve this goal, we need to understand how human behavior is generated, analyze tasks running our nerves and how they relate to them. Then and only then can we implement these mechanisms in robotic beings. In this study, we propose a model of competencies based on human neuroregulator system for analysis and decomposition of behavior into functional modules. Using this model allow separate and locate the tasks to be implemented in a robot that displays human-like behavior. As an example, we show the application of model to the autonomous movement behavior on unfamiliar environments and its implementation in various simulated and real robots with different physical configurations and physical devices of different nature. The main result of this study has been to build a model of competencies that is being used to build robotic systems capable of displaying behaviors similar to humans and consider the specific characteristics of robots.

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Federal Aviation Administration, Washington, D.C.

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"Partial bibliography": p. 425-436.

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"NAVTRA 10058-A"