1,721,346 research outputs found

    Communicating the ontological narrative of Ebola: An emerging disease in the time of “Epidemic 2.0”

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    In this article, we critically analyze the implications of “Epidemic 2.0”—specifically the formative role of social media (as an exemplar of Web 2.0 technology) in disseminating information during epidemics. We use a narrative analysis framework to study the Ebola-related messaging on the official Facebook pages of the World Health Organization (WHO) and the Center for Disease Control (CDC) in the wake of the recent epidemic in Western Africa. Using as our corpus all the messages on these pages between the period of July 1 and October 15, 2014, our analysis traces the development of an ontological Ebola narrative: a specific, historically contingent, ideological plot that reaffirms contemporary Western anxieties around emerging infections. Our analysis focuses on the evolution of this ontological narrative from a) consulting and containment, to b) an international concern, and c) the possibility of an epidemic in the United States

    Attitude control for a micromechanical flying insect via sensor output feedback

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    In this paper, we study attitude stabilization strategies via output sensor feedback for micro aerial vehicles (MAVs), inch-size robots capable of autonomous flight. In order to compensate for the size and power limitations of MAVs, we introduce the ocelli and halteres, the body orientation and rotation sensing mechanisms used by flying insects. The analysis and simulations of these sensors show the feasibility of using such biologically inspired approaches to build biomimetic gyroscopes and angular position detectors. Finally, attitude stabilization techniques based on these sensors are proposed and successfully tested on an aerodynamic model for a micromechanical flying insect (NIFI). To the authors' knowledge, this is the first attempt in using output feedback from biomimetic devices with ocelli and halteres to achieve attitude stabilization in MAVs

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Optimal linear LQG control over lossy networks without packet acknowledgment

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    This paper is concerned with control applications over lossy data networks. Sensor data is transmitted to an estimation-control unit over a network, and control commands are issued to subsystems over the same network. Sensor and control packets may be randomly lost according to a Bernoulli process. In this context, the discrete-time linear quadratic Gaussian (LQG) optimal control problem is considered. It is known that in the scenario described above, and for protocols for which there is no acknowledgment of successful delivery of control packets (e.g. UDP-like protocols), the LQG optimal controller is in general nonlinear. However, the simplicity of a linear sub-optimal solution is attractive for a variety of applications. Accordingly, this paper characterizes the optimal linear static controller and compares its performance to the case when there is acknowledgment of delivery of packets (e.g. TCP-like protocols)
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