949 resultados para Analyzing human behavior


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Peer-reviewed

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The behavior of normal individuals and psychiatric patients vary in a similar way following power laws. The presence of identical patterns of behavioral variation occurring in individuals with different levels of activity is suggestive of self-similarity phenomena. Based on these findings, we propose that the human behavior in social context can constitute a system exhibiting self-organized criticality (SOC). The introduction of SOC concept in psychological theories can help to approach the question of behavior predictability by taking into consideration their intrinsic stochastic character. Also, the ceteris paribus generalizations characteristic of psychological laws can be seen as a consequence of individual level description of a more complex collective phenomena. Although limited, this study suggests that, if an adequate level of description is adopted, the complexity of human behavior can be more easily approached and their individual and social components can be more realistically modeled. (C) 2009 Elsevier Ltd. All rights reserved.

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Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

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This study considers the complex dynamics of work motivation. Forty-eight employees completed a work-motivation diary several times per day over a period of four weeks. The obtained time series were analysed using different methodologies derived from chaos theory (i.e. recurrence plots, Lyapunov exponents, correlation dimension and surrogate data). Results showed chaotic dynamics in 75% of cases. The findings confirm the universality of chaotic behavior within human behavior, challenge some of the underlying assumptions on which work motivation theories are based, and suggest that chaos theory may offer useful and relevant information on how this process is managed within organizations.

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In this thesis, "Human behavior on the Internet", the human anxiety is conceptualized. The following questions have guided the writing of the thesis: How humans behave with the Internet technology? What goes in their mind? What kinds of behaviors are shown while using the Internet? What is the role of the content on the Internet and especially what are the types of anxiety behavior on the Internet? By conceptualization this thesis aims to provide a model for studying whether humans show signs of less or exacerbated anxiety while using the Internet. The empirical part of this thesis was built on new developed model and user study that utilizes that model. For the user study, the target users were divided into two groups based on their skill level. The user study used both qualitative and quantitative research methods. The qualitative research was conducted using interviews and observational analysis. The quantitative research was conducted in three iterations by using questionnaires and surveys. These results suggest that the significance of human on using technology would be integral part of such a study. The study also suggests that Internet has lulled humans with the sense of dependency to greater extent. In particular, the results identified seven main areas of human anxiety. These forms of anxiety require further studies to encompass human anxiety in more detail.

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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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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.