The influence of crowd noise and experience upon refereeing decisions in football

Thirty pilots flew three simulated landing approaches under conditions of low, medium, and high workload. Workload conditions were created by varying time pressure and external communications requirements. Our interest was in how the pilots strategically managed or adapted to the increasing workload. We independently assessed the pilot's ranking of the priority of different discrete tasks during the approach and landing. Pilots were found to sacrifice some aspects of primary flight control as workload increased. For discrete tasks, increasing workload increased the amount of time in performing the high priority tasks, decreased the time in performing those of lowest priority, and did not affect duration of performance episodes or optimality of scheduling of tasks of any priority level. Individual differences analysis revealed that high-performing subjects scheduled discrete tasks earlier in the flight and shifted more often between different activities.

Strategic workload management and decision biases in aviation

This study investigates the ability of an individual to integrate probabilistic information from a number of sources, and focuses particularly on the extent to which this integration is influenced by display proximity in space, time, and object configuration. In support of the principle of compatibility of proximity, the data indicated that integration performance was clearly ordered according to the degree of display integrality: those in the more integral rectangle conditions were significantly better at integration than those in the bar graph condition. Proximity of space had little effect upon performance, whereas proximity in time significantly improved performance in all three format conditions. Speed stress significantly hindered performance in all three format conditions. Finally, memory for isolated unintegrated attributes of a cue was not harmed by the increasing integrality of the rectangle formats.

Display proximity in multicue information integration: the benefits of boxes

Expert judgment about uncertainty: Bayesian decision making in realistic settings.

The body of literature addressing human errors and their effect on system performance is listed and categorized. The following factors were considered in classifying the literature: (1) applicability-human performance prediction, performance analysis of man-machine system, man-machine reliability allocation, human-error data collection, or human-error overview, (2) system under consideration-human component only or both human and hardware and (3) type of task being performed-operational or maintenance work, continuous or discrete tasks, and full range of human behaviour or single functions like decision-making or signal detection. >

A literature survey of the human reliability component in a man-machine system

A normative 2-stage model for incorporating reliability measurements of data-reporting sources in a Bayesian inference system is presented. An experiment required human subjects to make intuitive inferences about two hypotheses on the basis of sample data which were reported with a given reliability. When compared with the optimal model, subjects exhibited systematic errors in estimating the diagnostic impact of less than perfectly reliable data. Their responses reflected the use of specific nonoptimal heuristic strategies to process the information. A utility function was added to the normative model to illustrate how a best choice might be made from among potential data-gathering experiments whose costs increase with their reliabilities. Recommendations for using computer aids to enhance efficiency in inference systems are made

Utilization of Reliability Measurements in Bayesian Inference: Models and Human Performance

: As part of an effort to provide improved techniques and methods for intelligence collection planning and intelligence analysis, an experiment was conducted to assess the effectiveness of traditional tactical intelligence indications for the analysis of conventional military operations Forty-six captains in the Intelligence Officers Advanced Course each assumed the role of staff officer in a G-2 section of an Infantry Division conducting a mobile defense in north-central West Germany Each officer estimated the probability that each of 49 separate indications listed in Field Manual 30-5, Combat Intelligence, would occur, given the aggressor's known course of action Each indication was evaluated with four separate courses of action--Attack, Defend, Delay, and Withdraw Eleven indications were evaluated twice with each course of action to provide an estimate of reliability The estimates made by individual officers were highly reliable However, the variability in the estimates made by different officers for the same indication was extremely high, with an average range of estimates greater than 7 on a 0 to 10 scale The logic underlying clusters of related indications could not be clearly identified for any of the four courses of action The findings reveal that current indications of conventional military operations are either poorly understood or intrinsically inadequate for use in contemporary intelligence operations, or both

The Perception of Tactical Intelligence Indications by Intelligence Officers

In unsupervised learning pattern recognition problems, the need arises for updating conditional density functions of uncertain parameters using probability density function mixtures. In general, the form of the density mixtures is not reproducing, invoking the need for unlimited system storage requirements. One suboptimal method for achieving limited storage is to restrict the uncertain parameters in question to come from finite sets of values. An alternate method is proposed for a class of problems and its performance is shown to converge to that of the optimum unlimited storage system. A generalization of the procedure is also discussed.

Ronald L. Spooner

Papers

Utilization of Reliability Measurements in Bayesian Inference: Models and Human Performance

The Perception of Tactical Intelligence Indications by Intelligence Officers

An Unsupervised Learning Problem Using Limited Storage Capacity