Relevant bibliographies by topics / Task and workload modeling

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  2. Dissertations / Theses
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Academic literature on the topic 'Task and workload modeling'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Task and workload modeling"

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Zhang, X., X. Qu, H. Xue, H. Zhao, T. Li, and D. Tao. "Modeling pilot mental workload using information theory." Aeronautical Journal 123, no. 1264 (June 2019): 828–39. http://dx.doi.org/10.1017/aer.2019.13.

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AbstractPredicting mental workload of pilots can provide cockpit designers with useful information to reduce the possibility of pilot error and cost of training, improve the safety and performance of systems, and increase operator satisfaction. We present a theoretical model of mental workload, using information theory, based on review investigations of how effectively task complexity, visual performance, and pilot experience predict mental workload. The validity of the model was confirmed based on data collected from pilot taxiing experiments. Experiments were performed on taxiing tasks in four different scenarios. Results showed that predicted values from the proposed mental workload model were highly correlated to actual mental workload ratings from the experiments. The findings indicate that the proposed mental workload model appears to be effective in the prediction of pilots’ mental workload over time.
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Tijerina, Louis, and Dev Kochhar. "A Measurement Systems Analysis of Total Shutter Open Time (TSOT) as a Distraction Metric for Visual-Manual Tasks." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 51, no. 24 (October 2007): 1545–49. http://dx.doi.org/10.1177/154193120705102407.

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The Total Shutter Open Time (TSOT) metric was examined for estimating the visual-manual distraction potential of in-vehicle devices. A measurement systems analysis was carried out on TSOT using data on thirteen visual-manual tasks from the CAMP Driver Workload Metrics Project. TSOT showed low test-retest reliability but high repeatability when data were averaged across persons by task. TSOT predicted task completion time, lane keeping, speed variation, total glance time, and number of glances away from the road while driving. Tasks were classified into higher and lower workload categories based on literature, analytical modeling, and engineering judgment. TSOT showed a high percentage of statistically significant pairwise differences between higher vs. lower workload tasks. Different classification rules were also applied to TSOT. The best rule to classify tasks as higher or lower workload consistent with prior prediction was one in which a mean TSOT > 7.5 seconds implied the task was of higher workload. These results illustrate a general procedure to assess driver workload measures in general and the usefulness of TSOT in particular.
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Karpinsky, Nicole D., Eric T. Chancey, and Yusuke Yamani. "Modeling Relationships among Workload, Trust, and Visual Scanning in an Automated Flight Task." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 1550–54. http://dx.doi.org/10.1177/1541931213601356.

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The present study explored relationships among operators’ workload, subjective trust, and visual scanning patterns during their interaction with imperfect automation in a low-fidelity flight simulation task. Participants performed both a manual tracking task and a secondary system monitoring task (automated; FA- vs. miss-prone) under high and low load conditions manipulated by central task demand. The high load condition produced, 1) less frequent saccades toward system monitoring, 2) greater subjective workload, and 3) lower levels of subjective trust, compared to the low load condition. A mediation analysis revealed that subjective workload mediated the effect of load on visual scanning patterns whereas subjective trust did not. The results imply that, when the central task demands more attention, operators strategically reduce sampling rates of information from the system monitoring task assisted by imperfect automation depending on their subjective workload but not on subjective trust.
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Laughery, K. Ronald. "Task Network Modeling as a Basis for Analyzing Operator Workload." Proceedings of the Human Factors Society Annual Meeting 33, no. 2 (October 1989): 110–14. http://dx.doi.org/10.1177/154193128903300224.

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This paper discusses a technique for predicting human workload which is based around task network modeling. Task network modeling allows task analyses to be simulated on a computer to study dynamic system behavior through the addition of information, primarily task time and sequencing. A technique was developed by McCracken and Aldrich (1984) and modified by Drews, Laughery, Kramme, and Archer (1985) which permits the inclusion of workload information into a task network model. From these workload models, one can make predictions about where points of excessive operator overload are likely to occur. However, the technique has undergone only limited empirical validation. In addition to presenting the basic technique, this paper will briefly describe a software tool for using the technique as well as the perceived theoretical shortcomings of the technique in its current form.
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Borghetti, Brett J., Joseph J. Giametta, and Christina F. Rusnock. "Assessing Continuous Operator Workload With a Hybrid Scaffolded Neuroergonomic Modeling Approach." Human Factors: The Journal of the Human Factors and Ergonomics Society 59, no. 1 (February 2017): 134–46. http://dx.doi.org/10.1177/0018720816672308.

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Objective: We aimed to predict operator workload from neurological data using statistical learning methods to fit neurological-to-state-assessment models. Background: Adaptive systems require real-time mental workload assessment to perform dynamic task allocations or operator augmentation as workload issues arise. Neuroergonomic measures have great potential for informing adaptive systems, and we combine these measures with models of task demand as well as information about critical events and performance to clarify the inherent ambiguity of interpretation. Method: We use machine learning algorithms on electroencephalogram (EEG) input to infer operator workload based upon Improved Performance Research Integration Tool workload model estimates. Results: Cross-participant models predict workload of other participants, statistically distinguishing between 62% of the workload changes. Machine learning models trained from Monte Carlo resampled workload profiles can be used in place of deterministic workload profiles for cross-participant modeling without incurring a significant decrease in machine learning model performance, suggesting that stochastic models can be used when limited training data are available. Conclusion: We employed a novel temporary scaffold of simulation-generated workload profile truth data during the model-fitting process. A continuous workload profile serves as the target to train our statistical machine learning models. Once trained, the workload profile scaffolding is removed and the trained model is used directly on neurophysiological data in future operator state assessments. Application: These modeling techniques demonstrate how to use neuroergonomic methods to develop operator state assessments, which can be employed in adaptive systems.
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Smyth, Christopher C. "Modeling Mental Workload and Task Performance for Indirect Vision Driving." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 45, no. 23 (October 2001): 1694–98. http://dx.doi.org/10.1177/154193120104502328.

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Wu, Changxu, and Yili Liu. "Usability Makeover of a Cognitive Modeling Tool." Ergonomics in Design: The Quarterly of Human Factors Applications 15, no. 2 (April 2007): 8–14. http://dx.doi.org/10.1177/106480460701500201.

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FEATURE AT A GLANCE: In this article, we describe a new software tool that was developed for modeling human performance and mental workload in single- and dual-task situations. The tool features an interactive interface and is based on psychological theory. Using this new modeling tool, in most cases, users can model and predict human performance and workload by clicking buttons to select options without needing to learn a new programming language. They can also visualize the information-processing state of the model during simulation and compare and evaluate the simulated human performance and mental workload for different user interface designs based on the simulation results.
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See, Judi E., and Michael A. Vidulich. "Assessment of Computer Modeling of Operator Mental Workload during Target Acquisition." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 41, no. 2 (October 1997): 1303–7. http://dx.doi.org/10.1177/1071181397041002128.

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The predictive validity of computer simulation modeling of operator mental workload and situational awareness (SA) during a simulated air-to-ground combat mission was assessed in the present study. In Phase I, 12 participants completed a series of combat missions in a laboratory flight simulator and provided subjective ratings of workload (using the SWAT) and SA (using the SART). In Phase II, computer models of the mission were constructed using the Micro Saint modeling tool. The visual, auditory, kinesthetic, cognitive, and psychomotor components of the workload associated with each task were estimated and used to obtain measures of average and peak workload. The results from the simulated combat missions versus the Micro Saint models were similar but not identical, indicating that the computer models were partially but not completely valid predictors of mental workload and SA. The computer modeling appeared to be a more effective predictor of SA rather than mental workload.
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Steinberg, Dick, Dan Donohoo, Laura Strater, and Alice Diggs. "Workload Thresholds for Human Performance Models." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 781–85. http://dx.doi.org/10.1177/1541931213601679.

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Human performance modeling (HPM) can be an effective tool to use for determining crew designs. Crew design includes determining the number of operators needed, the role of automation, and member task responsibilities required to operate a system. Without effective measures of performance and thresholds for assessing success, design decisions from HPM will be erroneous. Operator tasks can be assigned and allocated to crew members in a simulation to estimate the workload for each operator during a period of performance. The methods for determining when an operator exceeds workload thresholds create challenges for those using HPM for crew design. Some types of analysis have more clearly defined thresholds. For example, if a military operator has too many tasks to complete to effectively initiate countermeasures between the times they receive a warning until the time the threat arrives, they are overloaded and cannot complete their mission. However, many missions do not have such a severe penalty for not completing the tasks within a given time. For example, pharmacists, satellite managers, traffic managers, food service workers do not have such stringent task timing completion thresholds. For example, the penalty for a food service provider to be overloaded is typically extended wait times rather than risk of a loss of life. For these types of operational situations, determining overload is much more challenging. This paper describes a new workload thresholds for operator workflow models. It incorporates the vigilance effort, the maximum time a crew member will be fully loaded, and determining the maximum time worked without a break.
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Mallat, Charlotte, Julien Cegarra, Christophe Calmettes, and Rémi L. Capa. "A Curvilinear Effect of Mental Workload on Mental Effort and Behavioral Adaptability: An Approach With the Pre-Ejection Period." Human Factors: The Journal of the Human Factors and Ergonomics Society 62, no. 6 (July 1, 2019): 928–39. http://dx.doi.org/10.1177/0018720819855919.

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Objective We tested Hancock and Szalma’s mental workload model, which has never been experimentally validated at a global level with the measure of the pre-ejection period (PEP), an index of beta-adrenergic sympathetic impact. Background Operators adapt to mental workload. When mental workload level increases, behavioral and physiological adaptability intensifies to reduce the decline in performance. However, if the mental workload exceeds an intermediate level, behavioral and physiological adaptability will decrease to protect individuals from excessive perturbations. This decrease is associated with a change in behavioral strategies and disengagement. Method The experimental task was a modified Fitts’ task used in Hancock and Caird. Five levels of task difficulty were computed. Behavioral and physiological adaptability was indexed by the performance with speed–accuracy trade-off and PEP reactivity. Results A curvilinear effect of task difficulty on PEP reactivity was significant, with high reactivity at the intermediate level but low reactivity at other levels. We observed a linear effect of task difficulty on error rate and a curvilinear effect on movement time. A decline in performance was noted up to the intermediate level, with a speed–accuracy trade-off above this level showing a faster movement time. Conclusion We observed for the first time behavioral and physiological adaptability as a function of mental workload. Application The results have important implications for the modeling of mental workload, particularly in the context of the performance-sensitive domain (car driving and air traffic control). They can help guide the design of human–computer interaction to maximize adaptive behavior, that is, the “comfort zone.”
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Dissertations / Theses on the topic "Task and workload modeling"

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Wojciechowski, Josephine Quinn. "Validation of a Task Network Human Performance Model of Driving." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/31713.

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Human performance modeling (HPM) is often used to investigate systems during all phases of development. HPM was used to investigate function allocation in crews for future combat vehicles. The tasks required by the operators centered around three primary functions, commanding, gunning, and driving. In initial investigations, the driver appeared to be the crew member with the highest workload. Validation of the driver workload model (DWM) is necessary for confidence in the ability of the model to predict workload. Validation would provide mathematical proof that workload of driving is high and that additional tasks impact the performance. This study consisted of two experiments. The purpose of each experiment was to measure performance and workload while driving and attending to an auditory secondary task. The first experiment was performed with a human performance model. The second experiment replicated the same conditions in a human-in-the-loop driving simulator. The results of the two experiments were then correlated to determine if the model could predict performance and workload changes. The results of the investigation indicate that there is some impact of an auditory task on driving. The model is a good predictor of mental workload changes with auditory secondary tasks. However, predictions of the impact on performance from secondary auditory tasks were not demonstrated in the simulator study. Frequency of the distraction was more influential in the changes of performance and workload than the demand of the distraction, at least under the conditions tested in this study. While the workload numbers correlate with simulator numbers, using the model would require a better understanding of what the workload changes would mean in terms of performance measures.
Master of Science
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Middlebrooks, Sam E. "Experimental Interrogation Of Network Simulation Models Of Human Task And Workload Performance In A U.S. Army Tactical Operations Center." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/34429.

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This thesis research is involved with the development of new methodologies for enhancing the experimental use of computer simulations to optimize predicted human performance in a work domain. Using a computer simulation called Computer modeling Of Human Operator System Tasks (CoHOST) to test the concepts in this research, methods are developed that are used to establish confidence limits and significance thresholds by having the computer model self report its limits. These methods, along with experimental designs that are tailored to the use of computer simulation instead of human subject based research, are used in the CoHOST simulation to investigate the U.S. Army battalion level command and control work domain during combat conditions and develop recommendations about that domain based on the experimental use of CoHOST with these methodologies. Further, with the realization that analytical results showing strictly numerical data do not always satisfy the need for understanding by those who could most benefit from the analysis, the results are further interpreted in accordance with a team performance model and the CoHOST analysis results are mapped to it according to macroergonomic and team performance concepts. The CoHOST computer simulation models were developed based on Army needs stemming from the Persian Gulf war. They examined human mental and physical performance capabilities resulting from the introduction of a new command and control vehicle with modernized digital communications systems. Literature searches and background investigations were conducted, and the CoHOST model architecture was developed that was based on a taxonomy of human performance. A computer simulation design was implemented with these taxonomic based descriptors of human performance in the military command and control domain using the commercial programming language MicroSaintâ ¢. The original CoHOST development project developed results that suggested that automation alone does not necessarily improve human performance. The CoHOST models were developed to answer questions about whether human operators could operate effectively in a specified work domain. From an analytical point of view this satisfied queries being made from the developers of that work domain. However, with these completed models available, the intriguing possibility now exists to allow an investigation of how to optimize that work domain to maximize predicted human performance. By developing an appropriate experimental design that allows evaluative conditions to be placed on the simulated human operators in the computer model rather than live human test subjects, a series of computer runs are made to establish test points for identified dependent variables against specified independent variables. With these test points a set of polynomial regression equations are developed that describe the performance characteristics according to these dependent variables of the human operator in the work domain simulated in the model. The resulting regression equations are capable of predicting any outcome the model can produce. The optimum values for the independent variables are then determined that produce the maximum predicted human performance according to the dependent variables. The conclusions from the CoHOST example in this thesis complement the results of the original CoHOST study with the prediction that the primary attentional focus of the battalion commander during combat operations is on establishing and maintaining an awareness and understanding of the situational picture of the battlefield he is operating upon. Being able to form and sustain an accurate mental model of this domain is the predicted predominant activity and drives his ability to make effective decisions and communicate those decisions to the other members of his team and to elements outside his team. The potential specific benefit of this research to the Army is twofold. First, the research demonstrates techniques and procedures that can be used without any required modifications to the existing computer simulations that allow significant predictive use to be made of the simulation beyond its original purpose and intent. Second, the use of these techniques with CoHOST is developing conclusions and recommendations from that simulation that Army force developers can use with their continuing efforts to improve and enhance the ability of commanders and other decision makers to perform as new digital communications systems and procedures are producing radical changes to the paradigm that describes the command and control work domain. The general benefits beyond the Army domain of this research fall into the two areas of methodological improvement of simulation based experimental procedures and in the actual application area of the CoHOST simulation. Tailoring the experimental controls and development of interrogation techniques for the self-reporting and analysis of simulation parameters and thresholds are topics that bode for future study. The CoHOST simulation, while used in this thesis as an example of new and tailored techniques for computer simulation based research, has nevertheless produced conclusions that deviate somewhat from prevailing thought in military command and control. Refinement of this simulation and its use in an even more thorough simulation based study could further address whether the military decision making process itself or contributing factors such as development of mental models for understanding of the situation is or should be the primary focus of team decision makers in the military command and control domain.
Master of Science
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Chakraborty, Sayan. "Experimental modeling of EVA tasks and workload using force-torque sensing apparatus." Thesis, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/42457.

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van, Lint J. W. C., and S. C. Calvert. "A generic multi-level framework for microscopic traffic simulation—Theory and an example case in modelling driver distraction." Elsevier, 2018. https://publish.fid-move.qucosa.de/id/qucosa%3A72789.

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Incorporation of more sophisticated human factors (HF) in mathematical models for driving behavior has become an increasingly popular and important research direction in the last few years. Such models enable us to simulate under which conditions perception errors and risk-taking lead to interactions that result in unsafe traffic conditions and ultimately accidents. In this paper, we present a generic multi-level microscopic traffic modelling and simulation framework that supports this important line of research. In this framework, the driving task is modeled in a multi-layered fashion. At the highest level, we have idealized (collision-free) models for car following and other driving tasks. These models typically contain HF parameters that exogenously “govern the human factor”, such as reaction time, sensitivities to stimuli, desired speed, etc. At the lowest level, we define HF variables (task demand and capacity, awareness) with which we maintain what the information processing costs are of performing driving tasks as well as non-driving related tasks such as distractions. We model these costs using so-called fundamental diagrams of task demand. In between, we define functions that govern the dynamics of the high-level HF parameters with these HF variables as inputs. When total task demand increases beyond task capacity, first awareness may deteriorate, where we use Endsley's three-level awareness construct to differentiate between effects on perception, comprehension, anticipation and reaction time. Secondly, drivers may adapt their response in line with Fullers risk allostasis theory to reduce risk to acceptable levels. This framework can be viewed as a meta model, that provides the analyst possibilities to combine and mix a wide variety of microscopic models for driving behavior at different levels of sophistication, depending on which HF are studied, and which phenomena need to be reproduced. We illustrate the framework with a distraction (rubbernecking) case. Our results show that the framework results in endogenous mechanisms for inter- and intra-driver differences in driving behavior and can generate multiple plausible HF mechanisms to explain the same observable traffic phenomena and congestion patterns that arise due to the distraction. We believe our framework can serve as a valuable tool in testing hypotheses related to the effects of HF on traffic efficiency and traffic safety in a systematic way for both the traffic flow and HF community.
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Middlebrooks, Sam E. "The COMPASS Paradigm For The Systematic Evaluation Of U.S. Army Command And Control Systems Using Neural Network And Discrete Event Computer Simulation." Diss., Virginia Tech, 2003. http://hdl.handle.net/10919/26605.

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In todayâ s technology based society the rapid proliferation of new machines and systems that would have been undreamed of only a few short years ago has become a way of life. Developments and advances especially in the areas of digital electronics and micro-circuitry have spawned subsequent technology based improvements in transportation, communications, entertainment, automation, the armed forces, and many other areas that would not have been possible otherwise. This rapid â explosionâ of new capabilities and ways of performing tasks has been motivated as often as not by the philosophy that if it is possible to make something better or work faster or be more cost effective or operate over greater distances then it must inherently be good for the human operator. Taken further, these improvements typically are envisioned to consequently produce a more efficient operating system where the human operator is an integral component. The formal concept of human-system interface design has only emerged this century as a recognized academic discipline, however, the practice of developing ideas and concepts for systems containing human operators has been in existence since humans started experiencing cognitive thought. An example of a human system interface technology for communication and dissemination of written information that has evolved over centuries of trial and error development, is the book. It is no accident that the form and shape of the book of today is as it is. This is because it is a shape and form readily usable by human physiology whose optimal configuration was determined by centuries of effort and revision. This slow evolution was mirrored by a rate of technical evolution in printing and elsewhere that allowed new advances to be experimented with as part of the overall use requirement and need for the existence of the printed word and some way to contain it. Today, however, technology is advancing at such a rapid rate that evolutionary use requirements have no chance to develop along side the fast pace of technical progress. One result of this recognition is the establishment of disciplines like human factors engineering that have stated purposes and goals of systematic determination of good and bad human system interface designs. However, other results of this phenomenon are systems that get developed and placed into public use simply because new technology allowed them to be made. This development can proceed without a full appreciation of how the system might be used and, perhaps even more significantly, what impact the use of this new system might have on the operator within it. The U.S. Army has a term for this type of activity. It is called â stove-piped developmentâ . The implication of this term is that a system gets developed in isolation where the developers are only looking â upâ and not â aroundâ . They are thus concerned only with how this system may work or be used for its own singular purposes as opposed to how it might be used in the larger community of existing systems and interfaces or, even more importantly, in the larger community of other new systems in concurrent development. Some of the impacts for the Army from this mode of system development are communication systems that work exactly as designed but are unable to interface to other communications systems in other domains for battlefield wide communications capabilities. Having communications systems that cannot communicate with each other is a distinct problem in its own right. However, when developments in one industry produce products that humans use or attempt to use with products from totally separate developments or industries, the Army concept of product development resulting from stove-piped design visions can have significant implication on the operation of each system and the human operator attempting to use it. There are many examples that would illustrate the above concept, however, one that will be explored here is the Army effort to study, understand, and optimize its command and control (C2) operations. This effort is at the heart of a change in the operational paradigm in C2 Tactical Operations Centers (TOCs) that the Army is now undergoing. For the 50 years since World War II the nature, organization, and mode of the operation of command organizations within the Army has remained virtually unchanged. Staffs have been organized on a basic four section structure and TOCs generally only operate in a totally static mode with the amount of time required to move them to keep up with a mobile battlefield going up almost exponentially from lower to higher command levels. However, current initiatives are changing all that and while new vehicles and hardware systems address individual components of the command structures to improve their operations, these initiatives do not necessarily provide the environment in which the human operator component of the overall system can function in a more effective manner. This dissertation examines C2 from a system level viewpoint using a new paradigm for systematically examining the way TOCs operate and then translating those observations into validated computer simulations using a methodological framework. This paradigm is called COmputer Modeling Paradigm And Simulation of Systems (COMPASS). COMPASS provides the ability to model TOC operations in a way that not only includes the individuals, work groups and teams in it, but also all of the other hardware and software systems and subsystems and human-system interfaces that comprise it as well as the facilities and environmental conditions that surround it. Most of the current literature and research in this area focuses on the concept of C2 itself and its follow-on activities of command, control, communications (C3), command, control, communications, and computers (C4), and command, control, communications, computers and intelligence (C4I). This focus tends to address the activities involved with the human processes within the overall system such as individual and team performance and the commanderâ s decision-making process. While the literature acknowledges the existence of the command and control system (C2S), little effort has been expended to quantify and analyze C2Ss from a systemic viewpoint. A C2S is defined as the facilities, equipment, communications, procedures, and personnel necessary to support the commander (i.e., the primary decision maker within the system) for conducting the activities of planning, directing, and controlling the battlefield within the sector of operations applicable to the system. The research in this dissertation is in two phases. The overall project incorporates sequential experimentation procedures that build on successive TOC observation events to generate an evolving data store that supports the two phases of the project. Phase I consists of the observation of heavy maneuver battalion and brigade TOCs during peacetime exercises. The term â heavy maneuverâ is used to connotate main battle forces such as armored and mechanized infantry units supported by artillery, air defense, close air, engineer, and other so called combat support elements. This type of unit comprises the main battle forces on the battlefield. It is used to refer to what is called the conventional force structure. These observations are conducted using naturalistic observation techniques of the visible functioning of activities within the TOC and are augmented by automatic data collection of such things as analog and digital message traffic, combat reports generated by the computer simulations supporting the wargame exercise, and video and audio recordings where appropriate and available. Visible activities within the TOC include primarily the human operator functions such as message handling activities, decision-making processes and timing, coordination activities, and span of control over the battlefield. They also include environmental conditions, functional status of computer and communications systems, and levels of message traffic flows. These observations are further augmented by observer estimations of such indicators as perceived level of stress, excitement, and level of attention to the mission of the TOC personnel. In other words, every visible and available component of the C2S within the TOC is recorded for analysis. No a priori attempt is made to evaluate the potential significance of each of the activities as their contribution may be so subtle as to only be ascertainable through statistical analysis. Each of these performance activities becomes an independent variable (IV) within the data that is compared against dependent variables (DV) identified according to the mission functions of the TOC. The DVs for the C2S are performance measures that are critical combat tasks performed by the system. Examples of critical combat tasks are â attacking to seize an objectiveâ , â seizure of key terrainâ , and â river crossingsâ . A list of expected critical combat tasks has been prepared from the literature and subject matter expert (SME) input. After the exercise is over, the success of these critical tasks attempted by the C2S during the wargame are established through evaluator assessments, if available, and/or TOC staff self analysis and reporting as presented during after action reviews. The second part of Phase I includes datamining procedures, including neural networks, used in a constrained format to analyze the data. The term constrained means that the identification of the outputs/DV is known. The process was to identify those IV that significantly contribute to the constrained DV. A neural network is then constructed where each IV forms an input node and each DV forms an output node. One layer of hidden nodes is used to complete the network. The number of hidden nodes and layers is determined through iterative analysis of the network. The completed network is then trained to replicate the output conditions through iterative epoch executions. The network is then pruned to remove input nodes that do not contribute significantly to the output condition. Once the neural network tree is pruned through iterative executions of the neural network, the resulting branches are used to develop algorithmic descriptors of the system in the form of regression like expressions. For Phase II these algorithmic expressions are incorporated into the CoHOST discrete event computer simulation model of the C2S. The programming environment is the commercial programming language Micro Saintä running on a PC microcomputer. An interrogation approach was developed to query these algorithms within the computer simulation to determine if they allow the simulation to reflect the activities observed in the real TOC to within an acceptable degree of accuracy. The purpose of this dissertation is to introduce the COMPASS concept that is a paradigm for developing techniques and procedures to translate as much of the performance of the entire TOC system as possible to an existing computer simulation that would be suitable for analyses of future system configurations. The approach consists of the following steps: · Naturalistic observation of the real system using ethnographic techniques. · Data analysis using datamining techniques such as neural networks. · Development of mathematical models of TOC performance activities. · Integration of the mathematical into the CoHOST computer simulation. · Interrogation of the computer simulation. · Assessment of the level of accuracy of the computer simulation. · Validation of the process as a viable system simulation approach.
Ph. D.
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Bowers, Drew. "Effects of Subjective Workload Measurement During a Workload Transition on Task Performance." University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1405001490.

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Guznov, Svyatoslav. "Teamwork in a RoboFlag Synthetic Task Environment." University of Cincinnati / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1236031728.

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Ungar, Nathaniel R. "Demand Transition, Tracking Accuracy, and Stress: Resource-Depletion and -Allocation Models." Cincinnati, Ohio : University of Cincinnati, 2005. http://www.ohiolink.edu/etd/view.cgi?acc%5Fnum=ucin1132255782.

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Thesis (M.A.)--University of Cincinnati, 2005.
Title from electronic thesis title page (viewed Sept. 6, 2007). Includes abstract. Keywords: dual-task; dual task; transition; transitions; demand transition; demand transitions; workload; mental workload; workload transition; workload transitions; task difficulty; tracking; tracking task; vigilance; compensatory tracking; performance; human performance; tracking performance; resource depletion; resource-depletion; mental resources; resource capacity; effort; effort-regulation; effort regulation; stress; transition stress; resource allocation; resource-allocation; human factors. Includes bibliographical references.
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Bowers, Margaret Anna. "The Effects of Workload Transitions in a Multitasking Environment." University of Dayton / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1374067692.

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Mears, Morgan. "The characterization and modeling of a parallel batch workload." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0002/MQ45519.pdf.

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Books on the topic "Task and workload modeling"

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Braby, Carole D. Cardiovascular and subjective measures of task demand in a low workload monitoring task: Summary report. Cranfield, U.K: College of Aeronautics, Cranfield Institute of Technology, 1987.

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Casper, Patricia A. Timesharing performance as an indicator of pilot mental workload. [Washington, DC: National Aeronautics and Space Administration, 1988.

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Casper, Patricia A. Timesharing performance as an indicator of pilot mental workload: Final report. [Washington, DC: National Aeronautics and Space Administration, 1989.

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Klose, G. Task-oriented modeling for natural language processing systems. Berlin: Technische Universität Berlin, Fachbereich 13--Informatik, 1993.

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Comstock, James R. The multi-attribute task battery for human operator workload and strategic behavior research. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1992.

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Comstock, James R. The multi-attribute task battery for human operator workload and strategic behavior research. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1992.

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Comstock, James R. The multi-attribute task battery for human operator workload and strategic behavior research. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1992.

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Comstock, James R. The multi-attribute task battery for human operator workload and strategic behavior research. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1992.

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Bierbaum, Carl R. Task analysis of the UH-60 mission and decision rules for developing a UH-60 workload prediction model. Alexandria, VA: U.S. Army Research Institute for the Behavioral and Social Sciences, 1989.

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International Institute for Applied Systems Analysis. Task Force Meeting on Input-Output Modeling. Input-output modeling: Proceedings of the Fifth IIASA Task Force Meeting on Input-Output Modeling. Berlin: Springer-Verlag, 1985.

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Book chapters on the topic "Task and workload modeling"

1

Amre, Shruti, and Ye Sun. "Effects of Non-driving Task Related Workload and Situational Awareness in Semi-autonomous Vehicles." In Advances in Simulation and Digital Human Modeling, 247–54. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79763-8_30.

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Lin, Jinchao, Gerald Matthews, Daniel Barber, and Niav Hughes. "Comparing the Sensitivity of Workload Measures for Different Task Types Using Nuclear Power Plant Main Control Room Simulators." In Advances in Simulation and Digital Human Modeling, 161–70. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79763-8_19.

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Lima, Pedro U. "Robot Task Modeling." In Encyclopedia of Robotics, 1–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-642-41610-1_9-1.

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Aikat, Jay, Kevin Jeffay, and F. Donelson Smith. "Workload Modeling and Traffic Generation." In The Effects of Traffic Structure on Application and Network Performance, 37–68. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-1848-1_3.

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Calzarossa, M., G. Haring, and G. Serazzi. "Workload Modeling for Computer Networks." In Architektur und Betrieb von Rechensystemen, 324–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73451-9_24.

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Feitelson, Dror G. "Workload Modeling for Performance Evaluation." In Performance Evaluation of Complex Systems: Techniques and Tools, 114–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45798-4_6.

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Salza, S., and M. Terranova. "Chapter 4 Database workload modeling." In Database Machine Performance: Modeling Methodologies and Evaluation Strategies, 50–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/3-540-17942-9_14.

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Jann, Joefon, Pratap Pattnaik, Hubertus Franke, Fang Wang, Joseph Skovira, and Joseph Riordan. "Modeling of workload in MPPs." In Job Scheduling Strategies for Parallel Processing, 95–116. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63574-2_18.

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Reniers, Vincent, Dimitri Van Landuyt, Ansar Rafique, and Wouter Joosen. "A Workload-Driven Document Database Schema Recommender (DBSR)." In Conceptual Modeling, 471–84. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62522-1_35.

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Santiputri, Metta, Aditya K. Ghose, Hoa Khanh Dam, and Xiong Wen. "Mining Process Task Post-Conditions." In Conceptual Modeling, 514–27. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25264-3_38.

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Conference papers on the topic "Task and workload modeling"

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Lin, Xiaoyang, Piyuan Lin, Peijie Huang, Linxiao Chen, Ziwei Fan, and Peisen Huang. "Modeling the Task of Google MapReduce Workload." In 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid). IEEE, 2015. http://dx.doi.org/10.1109/ccgrid.2015.104.

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Bauschat, J. M. "On the dependence of pilot task and pilot workload." In AIAA Modeling and Simulation Technologies Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2001. http://dx.doi.org/10.2514/6.2001-4189.

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Verma, Anoop, and Rahul Rai. "Modeling Multi Operator-Multi-UAV (MOMU) Operator Attention Allocation Problem." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-63810.

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This paper addresses the operator-task attention allocation problem in multiple operators managing multiple unmanned aerial vehicles (MOMU) setting. Previous works related to UAV operator-task attention allocation are mainly focused on single operator single UAV (SOSU) or single operator multiple UAVs (SOMU) models with emphasis on reward maximization only. Present research addresses two important issues viz. multi-operator paradigm, and workload imbalance in MOMU task attention allocation problem. Assigning multiple operators to multiple UAVs can improve the flexibility of human-system decision making. This added flexibility comes at a cost of added modeling complexity. Specifically, we consider important issue of operator workload imbalance in a team setting. We model workload imbalance in MOMU setting and through computational simulations show a balance between reward maximization and operators’ workload minimization is possible.
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Diaz, Manuel, Neal Takamoto, and Barbara Woolford. "Validation of task network modeling and workload component scaling in the assessment of the workload imposed during the Hubble Space Telescope servicing mission." In Space Programs and Technologies Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-4664.

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Volovich, Konstantin. "ESTIMATION OF THE WORKLOAD OF A HYBRID COMPUTING CLUSTER IN TASKS OF MODELING IN MATERIALS SCIENCE." In Mathematical modeling in materials science of electronic component. LLC MAKS Press, 2020. http://dx.doi.org/10.29003/m1511.mmmsec-2020/30-33.

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The article is devoted to methods of calculation and evaluation of the effectiveness of the functioning of hybrid computing systems. The article proposes a method of calculating the value of the workload using peak values of the cluster performance. The results and the quality of the functioning of cloud scientific services of high-performance computing using the roofline model are analyzed.
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Taeho Hwang, Miyoung Kim, Minsu Hwangbo, and Eunmi Oh. "Comparative analysis of cognitive tasks for modeling mental workload with electroencephalogram." In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2014. http://dx.doi.org/10.1109/embc.2014.6944170.

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Lucchese, A., G. Mossa, G. Mummolo, and F. P. Sisto. "A Shannon entropy graph-based model to evaluate the operator mental workload involved in procedure-guided tasks." In The 32nd European Modeling & Simulation Symposium. CAL-TEK srl, 2020. http://dx.doi.org/10.46354/i3m.2020.emss.014.

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Wang, Ke, Zhangjie Ma, and Ioan Raicu. "Modeling Many-Task Computing Workloads on a Petaflop IBM Blue Gene/P Supercomputer." In 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW). IEEE, 2013. http://dx.doi.org/10.1109/ipdpsw.2013.274.

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Taheri, Ehsan, Oleg Gusikhin, and Ilya Kolmanovsky. "Failure Prognostics for In-Tank Fuel Pumps of the Returnless Fuel Systems." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9725.

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With the motivation to develop Condition Based Maintenance (CBM) strategies for the automotive vehicles, this paper considers a data-driven approach to the prognostics of the automotive fuel pumps. Focusing on the returnless type fuel delivery systems, our approach is based on estimating the fuel pump workload based on the model learned from the past driving history. Statistical reliability models are then exploited to estimate failure probability. These models are formulated in terms of the workload and updated from data available from vehicles in the field. Numerical examples which illustrate the proposed methodology are reported. Compared to alternative approaches, which are based on detailed physics-based degradation modeling and/or electrical signal analysis, our approach is data-driven, exploits connected vehicle analytics and reliability-based modeling, and has a potential to lead to simpler implementations.
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Truschzinski, Martina. "Modeling Workload." In HRI '17: ACM/IEEE International Conference on Human-Robot Interaction. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3029798.3038408.

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Reports on the topic "Task and workload modeling"

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Middlebrooks, Sam E., Beverly G. Knapp, B. Diane Barnette, Cheryl A. Bird, and Joyce M. Johnson. CoHOST (Computer Modeling of Human Operator System Tasks) Computer Simulation Models to Investigate Human Performance Task and Workload Conditions in a U.S. Army Heavy Maneuver Battalion Tactical Operations Center. Fort Belvoir, VA: Defense Technical Information Center, August 1999. http://dx.doi.org/10.21236/ada368587.

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Schvaneveldt, Roger W., Gary B. Reid, Rebecca L. Gomez, and Sean Rice. Modeling Mental Workload. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada387269.

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Mitchell, Diane K. Mental Workload and ARL Workload Modeling Tools. Fort Belvoir, VA: Defense Technical Information Center, April 2000. http://dx.doi.org/10.21236/ada377300.

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Parasuraman, Raja, and Ericka Rovira. Workload Modeling and Workload Management: Recent Theoretical Developments. Fort Belvoir, VA: Defense Technical Information Center, April 2005. http://dx.doi.org/10.21236/ada432181.

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Jung, L. EPA short-term Task 2: workload capacity and telecommunication analyses. Office of Scientific and Technical Information (OSTI), September 1986. http://dx.doi.org/10.2172/5153356.

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Bierbaum, Carl R., and David B. Hamilton. Task Analysis and Workload Prediction for the MH-47E Mission and a Comparison with CH-47D Workload Predictions. Volume 1. Summary Report. Fort Belvoir, VA: Defense Technical Information Center, March 1991. http://dx.doi.org/10.21236/ada237500.

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Van Orden, K. F. Monitoring Moment-to-Moment Operator Workload Using Task Load and System-State Information. Fort Belvoir, VA: Defense Technical Information Center, June 2001. http://dx.doi.org/10.21236/ada390275.

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Bierbaum, Carl R., and David B. Hamilton. Task Analysis and Workload Prediction Model of the MH-60K Mission and a Comparison with UH-60A Workload Predictions. Volume 1. Summary Report. Fort Belvoir, VA: Defense Technical Information Center, October 1990. http://dx.doi.org/10.21236/ada241204.

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Hadgu, Teklu, Thomas Dewers, Steven Paul Gomez, and Edward N. Matteo. EBS Task Force: Task 9/FEBEX Modeling Final Report: Thermo-Hydrological Modeling with PFLOTRAN. Office of Scientific and Technical Information (OSTI), April 2020. http://dx.doi.org/10.2172/1615887.

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Klymyshyn, Nicholas A., Philip J. Jensen, and Nathan P. Barrett. Shaker Table Modeling Support Task 2015. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1494309.

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