33,165 research outputs found

    Modeling of the Terminal Velocities of the Dust Ejected Material by the Impact

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    We compute the distribution of velocities of the particles ejected by the impact of the projectile released from NASA Deep Impact spacecraft on the nucleus of comet 9P/Tempel 1 on the successive 20 hours following the collision. This is performed by the development and use of an ill-conditioned inverse problem approach, whose main ingredients are a set of observations taken by the Narrow Angle Camera (NAC) of OSIRIS onboard the Rosetta spacecraft, and a set of simple models of the expansion of the dust ejecta plume for different velocities. Terminal velocities are derived using a maximum likelihood estimator. We compare our results with published estimates of the expansion velocity of the dust cloud. Our approach and models reproduce well the velocity distribution of the ejected particles. We consider these successful comparisons of the velocities as an evidence for the appropriateness of the approach. This analysis provides a more thorough understanding of the properties of the Deep Impact dust cloud.Comment: Comments: 6 pages, 2 Postscript figures, To appear in the proceedings of "Deep Impact as a World Observatory Event - Synergies in Space, Time", ed. Hans Ulrich Kaeufl and Chris Sterken, Springer-Verla

    Norm-based and commitment-driven agentification of the Internet of Things

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    There are no doubts that the Internet-of-Things (IoT) has conquered the ICT industry to the extent that many governments and organizations are already rolling out many anywhere,anytime online services that IoT sustains. However, like any emerging and disruptive technology, multiple obstacles are slowing down IoT practical adoption including the passive nature and privacy invasion of things. This paper examines how to empower things with necessary capabilities that would make them proactive and responsive. This means things can, for instance reach out to collaborative peers, (un)form dynamic communities when necessary, avoid malicious peers, and be “questioned” for their actions. To achieve such empowerment, this paper presents an approach for agentifying things using norms along with commitments that operationalize these norms. Both norms and commitments are specialized into social (i.e., application independent) and business (i.e., application dependent), respectively. Being proactive, things could violate commitments at run-time, which needs to be detected through monitoring. In this paper, thing agentification is illustrated with a case study about missing children and demonstrated with a testbed that uses different IoT-related technologies such as Eclipse Mosquitto broker and Message Queuing Telemetry Transport protocol. Some experiments conducted upon this testbed are also discussed

    Belief Scheduler based on model failure detection in the TBM framework. Application to human activity recognition.

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    International audienceA tool called Belief Scheduler is proposed for state sequence recognition in the Transferable Belief Model (TBM) framework. This tool makes noisy temporal belief functions smoother using a Temporal Evidential Filter (TEF). The Belief Scheduler makes belief on states smoother, separates the states (assumed to be true or false) and synchronizes them in order to infer the sequence. A criterion is also provided to assess the appropriateness between observed belief functions and a given sequence model. This criterion is based on the conflict information appearing explicitly in the TBM when combining observed belief functions with predictions. The Belief Scheduler is part of a generic architecture developed for on-line and automatic human action and activity recognition in videos of athletics taken with a moving camera. In experiments, the system is assessed on a database composed of 69 real athletics video sequences. The goal is to automatically recognize running, jumping, falling and standing-up actions as well as high jump, pole vault, triple jump and {long jump activities of an athlete. A comparison with Hidden Markov Models for video classification is also provided

    SIGNIFICANT DOUBT ABOUT THE GOING CONCERN ASSUMPTION IN AUDIT

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    The purpose of this paper is to survey the going concern principle and its applicationin auditor’s work. The management of an entity is responsible for the assumption of the goingconcern principle in the compilation of the financial statements. We study the auditor’sresponsibilities in the audit of the financial statements relating to management’s use of the goingconcern assumption in the preparation of the financial statements. We analyze the events andconditions that may cause significant doubt about the ability of an entity to continue as a goingconcern.Professional judgment, Audit evidence, Management’s use of going concern assumption.

    Faculty and Student Perceptions of Technology Integration in Teaching

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    This journal article discusses a study examining the perceptions of faculty and students on the topic of technology integration in the teaching of courses at a Midwestern College of Education. The purposes of this study are to collect baseline data to identify the current extent of technology integration, to inform the strategic planning process, and for accreditation purposes. The article from "The Journal of Interactive Online Learning," describes faculty comfort levels and proficiency with technology, faculty perceptions and frequency with which they use technology, and student perceptions of technology use and impact on their learning. Educational levels: Graduate or professional
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