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At least 163 records · Page 9

Functional Task Tests in Partial Gravity During Parabolic Flight

BACKGROUND Understanding how critical mission tasks are performed in partial gravity such as on the moon or Mars is necessary to define effective and comprehensive countermeasure strategies for preserving crew performance during exploration missions. We studied the performance of tasks such as standing, balancing, walking, and jumping during the partial gravity phases of parabolic flight. We hypothesized that the acute effects of partial gravity on vestibular, proprioceptive, and sensorimotor functions would negatively impact performance. METHODS Twelve subjects (6F, 6M; 40.2 ± 8.5 years) were tested over three flights of 30 parabolas each, including 10 parabolas at 0.25g, 10 parabolas at 0.5g, and 10 parabolas at 0.75g. Subjects also performed tests in 1g between parabolas. During the seat egress and walk task, subjects rose from a seated position and walked as quickly as possible straight ahead towards a cone (4 m distance), stepped over a 30 cm high obstacle, walked around the cone making a 180° left turn, returned to the chair, and sat down in the chair. Other tasks included a tandem stance on rails, jump down from a 30cm platform, recovery from fall (prone to stand), and limits of stability tasks. Data were collected using inertial measurement units (Opal V2, APDM, Portland, OR) worn on the head and trunk, heart rate monitors (Polar, Finland), and a force plate (Bertec, Columbus, OH). During the jump down and limits of stability tasks, falls were recorded if subjects took extra steps, lifted their heels/toes, or used their arms to recover balance. RESULTS Gravity level had a significant effect on performance, with the greatest changes from 1g tending to be at the 0.25g level (Table 1). Lower gravity levels were associated with increased times to complete the seat egress and walk task and the recovery from fall task, increased head-trunk coordination, decreased tandem stance rail balance times, decreased change in heart rate during the recovery from fall task, and increased cone of stability distance in the anterior-posterior direction. In addition, there were significantly more falls recorded at the lower gravity levels: 31 falls at 0.25g, 14 falls at 0.5g, 6 falls at 0.75g, and 6 falls at 1g. DISCUSSION These data suggest that there is a dose-response relationship between gravity level and functional task performance. The largest changes in performance were expected at the lowest gravity level (0.25g) because subjects would no longer be able to use the gravitational reference for the perception of upright. Understanding the extent of performance deficits informs the risks and design of countermeasures for exploration spaceflight missions.

T R Macaulay↗

Characterizing the Performance of Executing Many-tasks on Summit

Many scientific workloads are comprised of many tasks, where each task is an independent simulation or analysis of data. The execution of millions of tasks on heterogeneous HPC platforms requires scalable dynamic resource management and multi-level scheduling. RADICAL-Pilot (RP) -- an implementation of the Pilot abstraction, addresses these challenges and serves as an effective runtime system to execute workloads comprised of many tasks. In this paper, we characterize the performance of executing many tasks using RP when interfaced with JSM and PRRTE on Summit: RP is responsible for resource management and task scheduling on acquired resource; JSM or PRRTE enact the placement of launching of scheduled tasks. Our experiments provide lower bounds on the performance of RP when integrated with JSM and PRRTE. Specifically, for workloads comprised of homogeneous single-core, 15 minutes-long tasks we find that: PRRTE scales better than JSM for > O(1000) tasks; PRRTE overheads are negligible; and PRRTE supports optimizations that lower the impact of overheads and enable resource utilization of 63% when executing O(16K), 1-core tasks over 404 compute nodes.

Matteo, Turilli↗

Remotely Teleoperating a Humanoid Robot to Perform Fine Motor Tasks with Virtual Reality - 18446

In this paper, we describe our ongoing work to develop cooperative control of NASA's R5 Valkyrie humanoid robot for performing dexterous manipulation tasks inside gloveboxes commonly found in many nuclear facilities. These tasks can be physically demanding and provide some element of risk to the operator when done by a person in situ. For example, if a glove is ruptured, the operator could be exposed to radioactive material. In many cases, the operator has low visibility and is unable to reach the entire task space, requiring the use of additional tools located inside the glovebox. Such tasks include cleaning particulate from inside the glovebox via sweeping or vacuuming, separating a specific amount of a compound to be weighed on a scale, or grasping and manipulating objects inside the glovebox. There is potential to move the operator to a nearby, safe location and instead place a humanoid robot in the potentially hazardous environment. However, teleoperating a humanoid robot to perform dexterous tasks at a comparable level to a human hand remains a difficult problem. Previous work for controlling humanoid robots often involves one or more operators using a standard 2D display with a mouse and keyboard as controllers. Successful interfaces use sensor fusion to provide information to the operator for increased situation awareness, but these designs have limitations. Gaining proper situation awareness by visualizing 3D information on a 2D screen requires time and increases the cognitive load on the user. Instead, if the operator is able to visualize and control the robot properly in three dimensions, it can increase situation and task awareness, reduce task time, reduce the chance of mistakes, and increase the likelihood of overall task success. We propose a two-part system that combines an HTC Vive virtual reality headset with either the Vive handheld controllers, or the Manus VR wearable gloves as the primary control. The operator wears the headset in a remote location and can visualize a reconstruction of the glovebox, created live by sensor scans from the robot and with sensors located inside the glovebox for a perspective traditionally unavailable to operators. By using the controllers or gloves to control the humanoid robots hands directly, they can plan actions in the virtual reconstruction. When the operator is satisfied with the plan, the actions are sent to the real robot. To test this system we have created a mockup of a glovebox that is accessible by Valkyrie, as well as several tasks that are a subsample of the tasks that might be required when working in a real glovebox. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout

We introduce a task-parallel algorithm for sparse incomplete Cholesky factorization that utilizes a 2D sparse partitioned-block layout of a matrix. Our factorization algorithm follows the idea of algorithms-by-blocks by using the block layout. The algorithm-byblocks approach induces a task graph for the factorization. These tasks are inter-related to each other through their data dependences in the factorization algorithm. To process the tasks on various manycore architectures in a portable manner, we also present a portable tasking API that incorporates different tasking backends and device-specific features using an open-source framework for manycore platforms i.e., Kokkos. A performance evaluation is presented on both Intel Sandybridge and Xeon Phi platforms for matrices from the University of Florida sparse matrix collection to illustrate merits of the proposed task-based factorization. Experimental results demonstrate that our task-parallel implementation delivers about 26.6x speedup (geometric mean) over single-threaded incomplete Choleskyby- blocks and 19.2x speedup over serial Cholesky performance which does not carry tasking overhead using 56 threads on the Intel Xeon Phi processor for sparse matrices arising from various application problems.

2D layout↗

Automatic Halo Management for the Uintah GPU-Heterogeneous Asynchronous Many-Task Runtime

The Uintah computational framework is used for the parallel solution of partial differential equations on adaptive mesh refinement grids using modern supercomputers. Uintah is structured with an application layer and a separate runtime system. Uintah is based on a distributed directed acyclic graph of computational tasks, with a task scheduler that efficiently schedules and executes these tasks on both CPU cores and on-node accelerators. The runtime system identifies task dependencies, creates a task graph prior to the execution of these tasks, automatically generates MPI message tags, and automatically performs halo transfers for simulation variables. Automating halo transfers in a heterogeneous environment poses significant challenges when tasks compute within a few milliseconds, as runtime overhead affects wall time execution, or when simulation variables require large halos spanning most or all of the computational domain, as task dependencies become expensive to process. These challenges are magnified at production scale when application developers require each compute node perform thousands of different halo transfers among thousands simulation variables. The principal contribution of this work is to (1) identify and address inefficiencies that arise when mapping tasks onto the GPU in the presence of automated halo transfers, (2) implement new schemes to reduce runtime system overhead, (3) minimize application developer involvement with the runtime, and (4) show overhead reduction results from these improvements.

Concurrency↗

TGE: Machine Learning Based Task Graph Embedding for Large-Scale Topology Mapping

Task mapping is an important problem in parallel and distributed computing. The goal in task mapping is to find an optimal layout of the processes of an application (or a task) onto a given network topology. We target this problem in the context of staging applications. A staging application consists of two or more parallel applications (also referred to as staging tasks) which run concurrently and exchange data over the course of computation. Task mapping becomes a more challenging problem in staging applications, because not only data is exchanged between the staging tasks, but also the processes of a staging task may exchange data with each other. We propose a novel method, called Task Graph Embedding (TGE), that harnesses the observable graph structures of parallel applications and network topologies. TGE employs a machine learning based algorithm to find the best representation of a graph, called an embedding, onto a space in which the task-to-processor mapping problem can be solved. We evaluate and demonstrate the effectiveness of TGE experimentally with the communication patterns extracted from runs of XGC, a large-scale fusion simulation code, on Titan.

Choi, Jong Youl↗

Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology

Purpose: Different computed tomography (CT) reconstruction techniques offer different image quality attributes of resolution and noise, challenging the ability to compare their dose reduction potential against each other. The purpose of this study was to evaluate and compare the task-based imaging performance of CT systems to enable the assessment of the dose performance of a model-based iterative reconstruction (MBIR) to that of an adaptive statistical iterative reconstruction (ASIR) and a filtered back projection (FBP) technique. Methods: The ACR CT phantom (model 464) was imaged across a wide range of mA setting on a 64-slice CT scanner (GE Discovery CT750 HD, Waukesha, WI). Based on previous work, the resolution was evaluated in terms of a task-based modulation transfer function (MTF) using a circular-edge technique and images from the contrast inserts located in the ACR phantom. Noise performance was assessed in terms of the noise-power spectrum (NPS) measured from the uniform section of the phantom. The task-based MTF and NPS were combined with a task function to yield a task-based estimate of imaging performance, the detectability index (d′). The detectability index was computed as a function of dose for two imaging tasks corresponding to the detection of a relatively small and a relatively large feature (1.5 and 25 mm, respectively). The performance of MBIR in terms of the d′ was compared with that of ASIR and FBP to assess its dose reduction potential. Results: Results indicated that MBIR exhibits a variability spatial resolution with respect to object contrast and noise while significantly reducing image noise. The NPS measurements for MBIR indicated a noise texture with a low-pass quality compared to the typical midpass noise found in FBP-based CT images. At comparable dose, the d′ for MBIR was higher than those of FBP and ASIR by at least 61% and 19% for the small feature and the large feature tasks, respectively. Compared to FBP and ASIR, MBIR indicated a 46%–84% dose reduction potential, depending on task, without compromising the modeled detection performance. Conclusions: The presented methodology based on ACR phantom measurements extends current possibilities for the assessment of CT image quality under the complex resolution and noise characteristics exhibited with statistical and iterative reconstruction algorithms. The findings further suggest that MBIR can potentially make better use of the projections data to reduce CT dose by approximately a factor of 2. Alternatively, if the dose held unchanged, it can improve image quality by different levels for different tasks.

60 APPLIED LIFE SCIENCES↗

Kokkos' Task DAG Capabilities.

This report documents the ASC/ATDM Kokkos deliverable "Production Portable Dy- namic Task DAG Capability." This capability enables applications to create and execute a dynamic task DAG ; a collection of heterogeneous computational tasks with a directed acyclic graph (DAG) of "execute after" dependencies where tasks and their dependencies are dynamically created and destroyed as tasks execute. The Kokkos task scheduler executes the dynamic task DAG on the target execution resource; e.g. a multicore CPU, a manycore CPU such as Intel's Knights Landing (KNL), or an NVIDIA GPU. Several major technical challenges had to be addressed during development of Kokkos' Task DAG capability: (1) portability to a GPU with it's simplified hardware and micro- runtime, (2) thread-scalable memory allocation and deallocation from a bounded pool of memory, (3) thread-scalable scheduler for dynamic task DAG, (4) usability by applications.

97 MATHEMATICS AND COMPUTING↗

GeoVision Analysis: Exploration Task Force Report

The GeoVision study effort included ground-breaking, detailed research on current and future market conditions and geothermal technologies in order to forecast and quantify the electric and non-electric deployment potentials under a range of scenarios, in addition to their impacts on the Nation’s jobs, economy and environment. Coordinated by the U.S. Department of Energy’s (DOE’s) Geothermal Technologies Office (GTO), the GeoVision study development relied on the collection, modeling, and analysis of robust datasets through seven national laboratory partners, which were organized into eight technical Task Force groups. The purpose of this report is to provide a central repository for the research conducted by the Exploration Task Force. The Exploration Task Force consists of four individuals representing three national laboratories: Patrick Dobson (task lead) and Christine Doughty of Lawrence Berkeley National Laboratory, Anna Wall of National Renewable Energy Laboratory, Travis McLing of Idaho National Laboratory, and Chester Weiss of Sandia National Laboratories. As part of the GeoVision analysis, our team conducted extensive scientific and financial analyses on a number of topics related to current and future geothermal exploration methods. The GeoVision Exploration Task Force complements the drilling and resource technology investigations conducted as part of the Reservoir Maintenance and Development Task Force. The Exploration Task Force however has focused primarily on early stage R&D technologies in exploration and confirmation drilling, along with an evaluation of geothermal financing challenges and assumptions, and innovative “blue-sky” technologies. This research was used to develop geothermal resource supply curves (through the use of GETEM) for use in the ReEDS capacity expansion modeling that determines geothermal technology deployment potential. It also catalogues and explores the large array of early-stage R&D technologies with the potential to dramatically reduce exploration and geothermal development costs, forming the basis of the GeoVision Technology Improvement (TI) scenario. These modeling topics are covered in detail in Potential to Penetration task force report. Most of the research contained herein has been published in peer-reviewed papers or conference proceedings and are cited and referenced accordingly. The sections that follow provide a central repository for all of the research findings of the Exploration and Confirmation Task Force. In summary, it provides a comprehensive discussion of Engineered Geothermal Systems (EGS) and associated technology challenges, the risks and costs of conducting geothermal exploration, a review of existing government efforts to date in advancing early-stage R&D in both exploration and EGS technologies, as well as a discussion of promising and innovative technologies and implementation of blue-sky concepts that could significantly reduce costs, lower risks, and shorten the time needed to explore and develop geothermal resources of all types.

15 GEOTHERMAL ENERGY↗

Status Report on Activities of the Systems Assessment Task Force, OECD-NEA Expert Group on Accident Tolerant Fuels for LWRs

The Organization for Economic Cooperation and Development /Nuclear Energy Agency (OECD/NEA) Nuclear Science Committee approved the formation of an Expert Group on Accident Tolerant Fuel (ATF) for LWRs (EGATFL) in 2014. Chaired by Kemal Pasamehmetoglu, INL Associate Laboratory Director for Nuclear Science and Technology, the mandate for the EGATFL defines work under three task forces: (1) Systems Assessment, (2) Cladding and Core Materials, and (3) Fuel Concepts. Scope for the Systems Assessment task force (TF1) includes definition of evaluation metrics for ATF, technology readiness level definition, definition of illustrative scenarios for ATF evaluation, and identification of fuel performance and system codes applicable to ATF evaluation. The identification of irradiation facilities around the world that are being used, or are planned to be used, for the irradiation testing of ATF cladding and fuel materials was later added to the TF1 scope (April 2017). The Cladding and Core Materials (TF2) and Fuel Concepts (TF3) task forces have worked to identify gaps and needs for modeling and experimental demonstration; define key properties of interest; identify the data necessary to perform concept evaluation under normal conditions and illustrative scenarios; identify available infrastructure (internationally) to support experimental needs; and make recommendations on priorities. Where possible, considering proprietary and other export restrictions (e.g., International Traffic in Arms Regulations), the Expert Group has facilitated the sharing of data and lessons learned across the international group membership. The Systems Assessment task force is chaired by Shannon Bragg-Sitton (Idaho National Laboratory [INL], U.S.), the Cladding Task Force is chaired by Marie Moatti (Electricite de France [EdF], France), and the Fuels Task Force is chaired by a Masaki Kurata (Japan Atomic Energy Agency [JAEA], Japan). The original Expert Group mandate was established for June 2014 to June 2016. In April 2016 the Expert Group voted to extend the mandate one additional year to June 2017 in order to complete the task force deliverables; this request was subsequently approved by the Nuclear Science Committee. All reports are currently in final draft and will be submitted to NEA for final formatting/editing in October 2017. A final EGATFL meeting will be held at NEA Headquarters in Paris, France on November 2-3, 2017 to resolve any final comments on the task force reports. This report provides brief summary of the Systems Assessment Task Force deliverable report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Evaluation of several secondary tasks in the determination of permissible time delays in simulator visual and motion cues

The effect of secondary tasks in determining permissible time delays in visual-motion simulation of a pursuit tracking task was examined. A single subject, a single set of aircraft handling qualities, and a single motion condition in tracking a target aircraft that oscillates sinusoidally in altitude were used. In addition to the basic simulator delays the results indicate that the permissible time delay is about 250 msec for either a tapping task, an adding task, or an audio task and is approximately 125 msec less than when no secondary task is involved. The magnitudes of the primary task performance measures, however, differ only for the tapping task. A power spectraldensity analysis basically confirms the result by comparing the root-mean-square performance measures. For all three secondary tasks, the total pilot workload was quite high.

Miller, G. K., Jr.↗

Short-term memory and dual task performance

Two hypotheses concerning the way in which short-term memory interacts with another task in a dual task situation are considered. It is noted that when two tasks are combined, the activity of controlling and organizing performance on both tasks simultaneously may compete with either task for a resource; this resource may be space in a central mechanism or general processing capacity or it may be some task-specific resource. If a special relationship exists between short-term memory and control, especially if there is an identity relationship between short-term and a central controlling mechanism, then short-term memory performance should show a decrement in a dual task situation. Even if short-term memory does not have any particular identity with a controlling mechanism, but both tasks draw on some common resource or resources, then a tradeoff between the two tasks in allocating resources is possible and could be reflected in performance. The persistent concurrence cost in memory performance in these experiments suggests that short-term memory may have a unique status in the information processing system.

Regan, J. E.↗

The effects of voice and manual control mode on dual task performance

Two fundamental principles of human performance, compatibility and resource competition, are combined with two structural dichotomies in the human information processing system, manual versus voice output, and left versus right cerebral hemisphere, in order to predict the optimum combination of voice and manual control with either hand, for time-sharing performance of a dicrete and continuous task. Eight right handed male subjected performed a discrete first-order tracking task, time-shared with an auditorily presented Sternberg Memory Search Task. Each task could be controlled by voice, or by the left or right hand, in all possible combinations except for a dual voice mode. When performance was analyzed in terms of a dual-task decrement from single task control conditions, the following variables influenced time-sharing efficiency in diminishing order of magnitude, (1) the modality of control, (discrete manual control of tracking was superior to discrete voice control of tracking and the converse was true with the memory search task), (2) response competition, (performance was degraded when both tasks were responded manually), (3) hemispheric competition, (performance degraded whenever two tasks were controlled by the left hemisphere) (i.e., voice or right handed control). The results confirm the value of predictive models invoice control implementation.

Wickens, C. D.↗

The Space Station Freedom evolution-phase - Crew-EVA demand for robotic substitution by task primitive

Space Station Freedom represents a significant demand for automation and robotics services as substitutes for crew EVAs. Results are reported from a study aimed at identifying the demand for crew EVA and the crew-task primitive distributions derived for input to future robotic substitution studies. Generic EVA tasks are developed from historical EVA mission timelines, and a set of 70 task primitives defined. The generic task activities are partitioned into task setup, kernel, and tear-down, with standardized task times and frequencies. These standardized times are coupled with inputs from numerous mission data bases in a probabilistic simulation to obtain estimates of total crew-EVA task time demand by crew task primitive. The use of probabilistic model is found to be crucial for understanding, isolating, and addressing the large uncertainties in the EVA task kernels.

Smith, Jeffrey H.↗

Evaluation of telerobotic systems using an instrumented task board

An instrumented task board was developed at NASA Marshall Space Flight Center (MSFC). An overview of the task board design, and current development status is presented. The task board was originally developed to evaluate operator performance using the Protoflight Manipulator Arm (PFMA) at MSFC. The task board evaluates tasks for Orbital Replacement Unit (ORU), fluid connect and transfers, electrical connect/disconnect, bolt running, and other basic tasks. The instrumented task board measures the 3-D forces and torques placed on the board, determines the robot arm's 3-D position relative to the task board using IR optics, and provides the information in real-time. The PFMA joint input signals can also be measured from a breakout box to evaluate the sensitivity or response of the arm operation to control commands. The data processing system provides the capability for post processing of time-history graphics and plots of the PFMA positions, the operator's actions, and the PFMA servo reactions in addition to real-time force/torque data presentation. The instrumented task board's most promising use is developing benchmarks for NASA centers for comparison and evaluation of telerobotic performance.

Carroll, John D.↗

Acquisition and production of skilled behavior in dynamic decision-making tasks

This status report consists of a thesis entitled 'Ecological Task Analysis: A Method for Display Enhancements.' Previous use of various analysis processes for the purpose of display interface design or enhancement has run the risk of failing to improve user performance due to the analysis resulting in only a sequencial listing of user tasks. Adopting an ecological approach to performing the task analysis, however, may result in the necessary modeling of an unpredictable and variable task domain required to improve user performance. Kirlik has proposed an Ecological Task Analysis framework which is designed for this purpose. It is the purpose of this research to measure this framework's effectiveness at enhancing display interfaces in order to improve user performance. Following the proposed framework, an ecological task analysis of experienced users of a complex and dynamic laboratory task, Star Cruiser, was performed. Based on this analysis, display enhancements were proposed and implemented. An experiment was then conducted to compare this new version of Star Cruiser to the original. By measuring user performance at different tasks, it was determined that during early sessions, use of the enhanced display contributed to better user performance compared to that achieved using the original display. Furthermore, the results indicate that the enhancements proposed as a result of the ecological task analysis affected user performance differently depending on whether they are enhancements which aid in the selection of a possible action or in the performance of an action. Generalizations of these findings to larger, more complex systems were avoided since the analysis was only performed on this one particular system.

Kirlik, Alex↗

Brain wave correlates of attentional states: Event related potentials and quantitative EEG analysis during performance of cognitive and perceptual tasks

The increased use of automation in the cockpits of commercial planes has dramatically decreased the workload requirements of pilots, enabling them to function more efficiently and with a higher degree of safety. Unfortunately, advances in technology have led to an unexpected problem: the decreased demands on pilots have increased the probability of inducing 'hazardous states of awareness.' A hazardous state of awareness is defined as a decreased level of alertness or arousal which makes an individual less capable of reacting to unique or emergency types of situations. These states tend to be induced when an individual is not actively processing information. Under such conditions a person is likely to let his/her mind wander, either to internal states or to irrelevant external conditions. As a result, they are less capable of reacting quickly to emergency situations. Since emergencies are relatively rare, and since the high automated cockpit requires progressively decreasing levels of engagement, the probability of being seduced into a lowered state of awareness is increasing. This further decreases the readiness of the pilot to react to unique circumstances such as system failures. The HEM Lab at NASA-Langley Research Center has been studying how these states of awareness are induced and what the physiological correlates of these different states are. Specifically, they have been interested in studying electroencephalographic (EEG) measures of different states of alertness to determine if such states can be identified and, hopefully, avoided. The project worked on this summer involved analyzing the EEG and the event related potentials (ERP) data collected while subjects performed under two conditions. Each condition required subjects to perform a relatively boring vigilance task. The purpose of using these tasks was to induce a decreased state of awareness while still requiring the subject to process information. Each task involved identifying an infrequently presented target stimulus. In addition to the task requirements, irrelevant tones were presented in the background. Research has shown that even though these stimuli are not attended, ERP's to them can still be elicited. The amplitude of the ERP waves has been shown to change as a function of a person's level of alertness. ERP's were also collected and analyzed for the target stimuli for each task. Brain maps were produced based on the ERP voltages for the different stimuli. In addition to the ERP's, a quantitative EEG (QEEG) was performed on the data using a fast Fourier technique to produce a power spectral analysis of the EEG. This analysis was conducted on the continuous EEG while the subjects were performing the tasks. Finally, a QEEG was performed on periods during the task when subjects indicated that they were in an altered state of awareness. During the tasks, subjects were asked to indicate by pressing a button when they realized their level of task awareness had changed. EEG epochs were collected for times just before and just after subjects made this reponse. The purpose of this final analysis was to determine whether or not subjective indices of level of awareness could be correlated with different patterns of EEG.

Freeman, Frederick G.↗

Attention in a multi-task environment

Two experiments used a low fidelity multi-task simulation to investigate the effects of cue specificity on task preparation and performance. Subjects performed a continuous compensatory tracking task and were periodically prompted to perform one of several concurrent secondary tasks. The results provide strong evidence that subjects enacted a strategy to actively divert resources towards secondary task preparation only when they had specific information about an upcoming task to be performed. However, this strategy was not as much affected by the type of task cued (Experiment 1) or its difficulty level (Experiment 2). Overall, subjects seemed aware of both the costs (degraded primary task tracking) and benefits (improved secondary task performance) of cue information. Implications of the present results for computational human performance/workload models are discussed.

Andre, Anthony D.↗