Tao Zhang
Publications by Tao Zhang (bibliography)
Harriott, Caroline E., Buford, Glenna L., Zhang, Tao and Adams, Julie A. (2012): Assessing workload in human-robot peer-based teams. In: Proceedings of the 7th International Conference on Human-Robot Interaction 2012. pp. 141-142.
“The effect of a robotic teammate on a human partner's workload has not been fully quantified. Prior research found that human participants experienced lower workload when working with a robotic partner than when working with a human partner. An evaluation investigated whether a similar trend in workload exists for tasks requiring direct and collaborative interaction between the partners, and joint team decision-making. The subjective results indicate a similar trend to the prior results; participants rated workload lower for the more complex task when partnered with a robot than when partnered with a human.”
© All rights reserved Harriott et al. and/or their publisher
Harriott, Caroline E., Buford, Glenna L., Zhang, Tao and Adams, Julie A. (2012): Human-human vs. human-robot teamed investigation. In: Proceedings of the 7th International Conference on Human-Robot Interaction 2012. pp. 405-406.
“Clips from an evaluation where participants, each paired with either a human or robot partner, were deployed to search a hallway for suspicious items, in a manner similar to tactics used by first responders handling bomb threats are presented. The teams used natural, verbal communication to collaborate, determine where hazards were located, and which items were suspicious. The video demonstrates that the investigations in both conditions played out in a similar manner and participants were able to complete the investigations successfully with a robot partner; however, sometimes the participants were uncertain how to interact with the robot.”
© All rights reserved Harriott et al. and/or their publisher
Harriott, Caroline E., Zhang, Tao and Adams, Julie A. (2011): Evaluating the applicability of current models of workload to peer-based human-robot teams. In: Proceedings of the 6th International Conference on Human Robot Interaction 2011. pp. 45-52.
“Human-Robot peer-based teams are evolving from a far-off possibility into a reality. Human Performance Moderator Functions (HPMFs) can be used to predict human behavior by incorporating the effects of internal and external influences such as fatigue and workload. The applicability of HPMFs to human-robot teams is not proven. The presented research focuses on determining the applicability of workload HPMFs in team tasks for first response mass casualty triage incidents between a Human-Human and a Human-Robot team. A model representing workload for each team was developed using IMPRINT Pro. The results from an empirical evaluation were compared to the model results. While significant differences between the two conditions were not found in all data, there was a general trend that workload in the human-robot condition was slightly lower than the workload experienced in the human-human condition. This trend was predicted by the IMPRINT Pro models. These results are the first to indicate that existing HPMFs can be applied to human-robot peer-based teams.”
© All rights reserved Harriott et al. and/or their publisher
Ramos, Heitor S., Zhang, Tao, Liu, Jie, Priyantha, Nissanka B. and Kansal, Aman (2011): LEAP: a low energy assisted GPS for trajectory-based services. In: Proceedings of the 2011 International Conference on Uniquitous Computing 2011. pp. 335-344.
“Trajectory-based services require continuous user location sensing. GPS is the most common outdoor location sensor on mobile devices. However, the high energy consumption of GPS sensing prohibits it to be used continuously in many applications. In this paper, we propose a Low Energy Assisted Positioning (LEAP) solution that carefully partitions the GPS signal processing pipeline and shifts delay tolerant position calculations to the cloud. The GPS receiver only needs to be on for less than a second to collect the sub-millisecond level propagation delay for each satellites signal. With a reference to a nearby object, such as a cell tower, the LEAP server can infer the rest of the information necessary to perform GPS position calculation. We analyze the accuracy and energy benefit of LEAP and use real user traces to show that LEAP can save up to 80% GPS energy consumption in typical trajectory-based service scenarios.”
© All rights reserved Ramos et al. and/or ACM Press
Xie, Xiaoyan, Lin, Fuzong and Zhang, Tao (2001): Comparison between on- and off-campus behaviour and adaptability in online learning: a case from China. In Behaviour and Information Technology, 20 (4) pp. 281-291.
“More and more universities and colleges are providing online courses not only for on-campus students but also for off-campus students. Tutors have to consider the differences between on- and off-campus students in order to improve effective instruction. Comparisons are made in this paper between on- and off-campus performances in online learning from four areas: learning time, path of browsing courseware, intercommunication and adaptability towards online learning. The last two areas are emphasized. Multiple approaches were adopted to collect data, which include questionnaires, posted documents, online logs, interviews and observations. This study shows that the rush time of online learning, paths of browsing courseware and favourite intercommunication means of on- and off-campus students are similar. But there are also some differences between these two groups such as competence of self-learning, enthusiasm of interpersonal exchange, dependence on tutors, feeling of learning stress, etc.”
© All rights reserved Xie et al. and/or Taylor and Francis
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