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En Route Air Traffic Control Mid-Term Job Task Analysis Download All Files (compressed zip)
Prepared for the Federal Aviation Administration, AJE-15. Washington, DC: Human Solutions Inc./Metron
  • Murphy, Elizabeth D.
  • Albert, Harold A.
  • Chen, Jennifer M.
  • Anderson, Gregory G.
  • Schultheis, Udo W.

Abstract (click)

In the process of modernizing air traffic control (ATC), as practiced in the domestic United States, the Federal Aviation Administration (FAA) is introducing a large suite of new technologies to upgrade the National Airspace System (NAS). Intended to improve the efficiency and effectiveness of ATC throughout the NAS, the new technologies include automated capabilities that will affect air traffic controllers' best practices. These new capabilities are supported by the En Route Automation Modernization (ERAM) system. This increasing automation can be expected to affect the controller's decision-making processes, the information used in decision making, and the mental workload experienced by controllers, as well as behavioral aspects of the controller's work. The controller will remain responsible for ensuring the safe, orderly and expeditious flow of air traffic in NAS airspace.


Primary Purpose and Use HSI conducted and documented this Job Task Analysis (JTA) for the FAA under the sponsorship of the En Route and Oceanic Services Program Operations System Engineering Group (AJE-13). The purpose of the JTA was to analyze changes to the controller's job and to document those changes within the context of the En Route controller's operational responsibilities. The projected changes include new information requirements arising from the introduction of new tools and technologies. A primary use of the JTA is to guide the design of user interfaces to the automated support that is intended to increase NAS efficiency and productivity.

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The Pervasiveness of 1/f Scaling in Speech Reflects the Metastable Basis of Cognition Download PDF
Cognitive Science; Nov2008, Vol. 32 Issue 7, p1217-1231, 15p, 1 Diagram, 6 Graphs Endnote Citation
  • Kello, Christopher T.
  • Anderson, Gregory G.
  • Holden, John G.
  • Van Orden, Guy C.

Abstract (click)

Human neural and behavioral activities have been reported to exhibit fractal dynamics known as "1/f noise," which is more aptly named "1/f scaling." Some argue that 1/f scaling is a general and pervasive property of the dynamical substrate from which cognitive functions are formed. Others argue that it is an idiosyncratic property of domain-specific processes.


An experiment was conducted to investigate whether 1/f scaling pervades the intrinsic fluctuations of a spoken word. Ten participants each repeated the word "bucket" over 1,000 times, and fluctuations in acoustic measurements across repetitions generally followed the 1/f scaling relation, including numerous parallel yet distinct series of 1/f fluctuations. On the basis of work showing that 1/f scaling is a universal earmark of metastability, it is proposed that the observed pervasiveness of 1/f fluctuations in speech reflects the fact that cognitive functions are formed as metastable patterns of activity in brain, body, and environment.

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Robot-directed speech: using language to assess first-time users' conceptualizations of a robot Download PDF

ACM/IEEE International Conference on Human-Robot Interaction
Proceeding of the 5th ACM/IEEE international conference on Human-robot interaction, Osaka, Japan Endnote Citation
  • Sarah Kriz University of Washington, Seattle, WA, USA
  • Gregory Anderson George Mason University, Fairfax, VA, USA
  • J. Gregory Trafton U.S. Naval Research Laboratory, Washington, DC, USA

Abstract (click)

It is expected that in the near-future people will have daily natural language interactions with robots. However, we know very little about how users feel they should talk to robots, especially users who have never before interacted with a robot. The present study evaluated first-time users' expectations about a robot's cognitive and communicative capabilities by comparing robot-directed speech to the way in which participants talked to a human partner.


The results indicate that participants spoke more loudly, raised their pitch, and hyperarticulated their messages when they spoke to the robot, suggesting that they viewed the robot as having low linguistic competence. However, utterances show that speakers often assumed that the robot had humanlike cognitive capabilities. The results suggest that while first-time users were concerned with the fragility of the robot's speech recognition system, they believed that the robot had extremely strong information processing capabilities.

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