25 research outputs found

    Combining Path Integration and Remembered Landmarks When Navigating without Vision

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    This study investigated the interaction between remembered landmark and path integration strategies for estimating current location when walking in an environment without vision. We asked whether observers navigating without vision only rely on path integration information to judge their location, or whether remembered landmarks also influence judgments. Participants estimated their location in a hallway after viewing a target (remembered landmark cue) and then walking blindfolded to the same or a conflicting location (path integration cue). We found that participants averaged remembered landmark and path integration information when they judged that both sources provided congruent information about location, which resulted in more precise estimates compared to estimates made with only path integration. In conclusion, humans integrate remembered landmarks and path integration in a gated fashion, dependent on the congruency of the information. Humans can flexibly combine information about remembered landmarks with path integration cues while navigating without visual information.National Institutes of Health (U.S.) (Grant T32 HD007151)National Institutes of Health (U.S.) (Grant T32 EY07133)National Institutes of Health (U.S.) (Grant F32EY019622)National Institutes of Health (U.S.) (Grant EY02857)National Institutes of Health (U.S.) (Grant EY017835-01)National Institutes of Health (U.S.) (Grant EY015616-03)United States. Department of Education (H133A011903

    Patient and stakeholder engagement learnings: PREP-IT as a case study

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    Acquistion of structural versus object landmark knowledge.

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    Weight given to path integration by individual participants.

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    <p>Amount of weight that individual subjects gave to location information obtained by path integration when viewed and walked locations were perceived as congruent versus incongruent.</p

    Participants' weighting of path integration in the combined cue task.

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    <p>Amount of weight (and 95% confidence interval) that participants gave to path integration in the combined cue task. Weights were computed from participants' estimates of their location in the hallway.</p

    Precision of estimates in the combined cue task.

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    <p>The variability (root mean squared error) of localization estimates collapsed across viewing conditions when: 1) no landmarks, 2) remembered landmarks were judged to be incongruent with path integration information, and 3) remembered landmarks were judged to be congruent with path integration.</p

    HovercRaft: Achieving Scalability and Fault-tolerance for microsecond-scale Datacenter Services

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    Cloud platform services must simultaneously be scalable, meet low tail latency service-level objectives, and be resilient to a combination of software, hardware, and network failures. Replication plays a fundamental role in meeting both the scalability and the fault-tolerance requirement, but is subject to opposing requirements: (1) scalability is typically achieved by relaxing consistency; (2) fault-tolerance is typically achieved through the consistent replication of state machines. Adding nodes to a system can therefore either in- crease performance at the expense of consistency, or increase resiliency at the expense of performance. We propose HovercRaft, a new approach by which adding nodes increases both the resilience and the performance of general-purpose state-machine replication. We achieve this through an extension of the Raft protocol that carefully eliminates CPU and I/O bottlenecks and load balances requests. Our implementation uses state-of-the-art kernel-bypass techniques, datacenter transport protocols, and in-network programmability to deliver up to 1 million operations/second for clusters of up to 9 nodes, linear speedup over unreplicated configuration for selected workloads, and a 4Ă— speedup for the YCSBE-E benchmark running on Redis over an unreplicated deployment
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