17,792 research outputs found

    Experimental analysis of dense multipath components in an industrial environment

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    This work presents an analysis of dense multipath components (DMC) in an industrial workshop. Radio channel sounding was performed with a vector network analyzer and virtual antenna arrays. The specular and dense multipath components were estimated with the RiMAX algorithm. The DMC covariance structure of the RiMAX data model was validated. Two DMC parameters were studied: the distribution of radio channel power between specular and dense multipath, and the DMC reverberation time. The DMC power accounted for 23% to 70% of the total channel power. A significant difference between DMC powers in line-of-sight and nonline-of-sight was observed, which can be largely attributed to the power of the line-of-sight multipath component. In agreement with room electromagnetics theory, the DMC reverberation time was found to be nearly constant. Overall, DMC in the industrial workshop is more important than in office environments: it occupies a fraction of the total channel power that is 4% to 13% larger. The industrial environment absorbs on average 29% of the electromagnetic energy compared to 45%-51% for office environments in literature: this results in a larger reverberation time in the former environment. These findings are explained by the highly cluttered and metallic nature of the workshop

    Teams organization and performance analysis in autonomous human-robot teams

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    This paper proposes a theory of human control of robot teams based on considering how people coordinate across different task allocations. Our current work focuses on domains such as foraging in which robots perform largely independent tasks. The present study addresses the interaction between automation and organization of human teams in controlling large robot teams performing an Urban Search and Rescue (USAR) task. We identify three subtasks: perceptual search-visual search for victims, assistance-teleoperation to assist robot, and navigation-path planning and coordination. For the studies reported here, navigation was selected for automation because it involves weak dependencies among robots making it more complex and because it was shown in an earlier experiment to be the most difficult. This paper reports an extended analysis of the two conditions from a larger four condition study. In these two "shared pool" conditions Twenty four simulated robots were controlled by teams of 2 participants. Sixty paid participants (30 teams) were recruited to perform the shared pool tasks in which participants shared control of the 24 UGVs and viewed the same screens. Groups in the manual control condition issued waypoints to navigate their robots. In the autonomy condition robots generated their own waypoints using distributed path planning. We identify three self-organizing team strategies in the shared pool condition: joint control operators share full authority over robots, mixed control in which one operator takes primary control while the other acts as an assistant, and split control in which operators divide the robots with each controlling a sub-team. Automating path planning improved system performance. Effects of team organization favored operator teams who shared authority for the pool of robots. © 2010 ACM

    Probabilistic priority assessment of nurse calls

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    Current nurse call systems are very static. Call buttons are fixed to the wall, and systems do not account for various factors specific to a situation. We have developed a software platform, the ontology-based Nurse Call System (oNCS), which supports the transition to mobile and wireless nurse call buttons and uses an intelligent algorithm to address nurse calls. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff and patients into account by using an ontology. This article describes a probabilistic extension of the oNCS that supports a more sophisticated nurse call algorithm by dynamically assigning priorities to calls based on the risk factors of the patient and the kind of call. The probabilistic oNCS is evaluated through implementation of a prototype and simulations, based on a detailed dataset obtained from 3 nursing departments of Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls among nurses, and the assignment of priorities to calls are compared for the oNCS and the current nurse call system. Additionally, the performance of the system and the parameters of the priority assignment algorithm are explored. The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the probabilistic oNCS significantly improves the assignment of nurses to calls. Calls generally result in a nurse being present more quickly, the workload distribution among the nurses improves, and the priorities and kinds of calls are taken into account

    Unlocking the deployment of spectrum sharing with a policy enforcement framework

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    Spectrum sharing has been proposed as a promising way to increase the efficiency of spectrum usage by allowing incumbent operators (IOs) to share their allocated radio resources with licensee operators (LOs), under a set of agreed rules. The goal is to maximize a common utility, such as the sum rate throughput, while maintaining the level of service required by the IOs. However, this is only guaranteed under the assumption that all “players”respect the agreed sharing rules. In this paper, we propose a comprehensive framework for licensed shared access (LSA) networks that discourages LO misbehavior. Our framework is built around three core functions: misbehavior detection via the employment of a dedicated sensing network; a penalization function; and, a behavior-driven resource allocation. To the best of our knowledge, this is the first time that these components are combined for the monitoring/policing of the spectrum under the LSA framework. Moreover, a novel simulator for LSA is provided as an open access tool, serving the purpose of testing and validating our proposed techniques via a set of extensive system-level simulations in the context of mobile network operators, where IOs and several competing LOs are considered. The results demonstrate that violation of the agreed sharing rules can lead to a great loss of resources for the misbehaving LOs, the amount of which is controlled by the system. Finally, we promote that including a policy enforcement function as part of the spectrum sharing system can be beneficial for the LSA system, since it can guarantee compliance with the spectrum sharing rules and limit the short-term benefits arising from misbehavior
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