2019
DOI: 10.1155/2019/4545917
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Coordinating Real-Time Serial Cooperative Work by Cuing the Order in the Case of Theatrical Performance Practice

Abstract: Our goal is to facilitate real-time serial cooperative work. In real-time serial cooperative work, the order of subtasks is important because a failure of the order leads to a failure of the whole task. So, coordinating the order of workers' subtasks is necessary to smoothly accomplish the tasks. In this paper, we propose a method that uses vibration to present the action order and coordinate the orders. We conducted a user study to verify the effectiveness of the method in theatrical performance practice, whi… Show more

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Cited by 2 publications
(2 citation statements)
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“…Meanwhile, big data stream processing systems (DSPSs) provide exact real-time data processing services. e statistical data from Seagate show that the total amount of data will reach 163 ZB before 2025 [2], a quarter of which will be generated by mobile information devices and require real-time processing [3]. erefore, to handle real-time mobile streaming data that exhibit volatility, burstiness, disorder, and infiniteness [4], DSPSs have been widely applied in multiple scenarios of big data stream computing, especially for mobile data processing.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Meanwhile, big data stream processing systems (DSPSs) provide exact real-time data processing services. e statistical data from Seagate show that the total amount of data will reach 163 ZB before 2025 [2], a quarter of which will be generated by mobile information devices and require real-time processing [3]. erefore, to handle real-time mobile streaming data that exhibit volatility, burstiness, disorder, and infiniteness [4], DSPSs have been widely applied in multiple scenarios of big data stream computing, especially for mobile data processing.…”
Section: Introductionmentioning
confidence: 99%
“…e algorithm calculates the initial capacity based on the network transmission performance and adjusts it by periodic feedback to determine an appropriate capacity for each edge, thus laying the foundation for the elastic resource reallocation algorithm. (3) We propose the elastic resource reallocation algorithm based on the resource allocation model. is algorithm optimally dispatches the increasing load and creates the resource-rescheduling plan by identifying the performance bottleneck, thus improving the performance by effectively utilizing computing resources.…”
Section: Introductionmentioning
confidence: 99%