Dissertations / Theses on the topic 'Task and workload modeling'

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

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

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.

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.

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.

MAGALHÃES, Deborah Maria Vieira. Workload modeling and prediction for resources provisioning in cloud. 2017. 100 f. Tese (Doutorado em Engenharia de Teleinformática)–Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2017.
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The evaluation of resource management policies in cloud environments is challenging since clouds are subject to varying demand coming from users with different profiles and Quality de Service (QoS) requirements. Factors as the virtualization layer overhead, insufficient trace logs available for analysis, and mixed workloads composed of a wide variety of applications in a heterogeneous environment frustrate the modeling and characterization of applications hosted in the cloud. In this context, workload modeling and characterization is a fundamental step on systematizing the analysis and simulation of the performance of computational resources management policies and a particularly useful strategy for the physical implementation of the clouds. In this doctoral thesis, we propose a methodology for workload modeling and characterization to create resource utilization profiles in Cloud. The workload behavior patterns are identified and modeled in the form of statistical distributions which are used by a predictive controller to establish the complex relationship between resource utilization and response time metric. To this end, the controller makes adjustments in the resource utilization to maintain the response time experienced by the user within an acceptable threshold. Hence, our proposal directly supports QoS-aware resource provisioning policies. The proposed methodology was validated through two different applications with distinct characteristics: a scientific application to pulmonary diseases diagnosis, and a web application that emulates an auction site. The performance models were compared with monitoring data through graphical and analytical methods to evaluate their accuracy, and all the models presented a percentage error of less than 10 %. The predictive controller was able to dynamically maintain the response time close to the expected trajectory without Service Level Agreement (SLA) violation with an Mean Absolute Percentage Error (MAPE) = 4.36%.
A avaliação de políticas de gerenciamento de recursos em nuvens computacionais é uma tarefa desafiadora, uma vez que tais ambientes estão sujeitos a demandas variáveis de usuários com diferentes perfis de comportamento e expectativas de Qualidade de Serviço (QoS). Fatores como overhead da camada de virtualização, indisponibilidade de dados e complexidade de cargas de trabalho altamente heterogêneas dificultam a modelagem e caracterização de aplicações hospedadas em nuvens. Neste contexto, caracterizar e modelar a carga de trabalho (ou simples- mente carga) é um passo importante na sistematização da análise e simulação do desempenho de políticas de gerenciamento dos recursos computacionais e uma estratégia particularmente útil antes da implantação física das nuvens. Nesta tese de doutorado, é proposta uma metodologia para modelagem e caracterização de carga visando criar perfis de utilização de recursos em Nuvem. Os padrões de comportamento das cargas são identificados e modelados sob a forma de distribuições estatísticas as quais são utilizadas por um controlador preditivo a fim de estabelecer a complexa relação entre a utilização dos recursos e a métrica de tempo de resposta. Desse modo, o controlador realiza ajustes no percentual de utilização do recursos a fim de manter o tempo de resposta observado pelo o usuário dentro de um limiar aceitável. Assim, nossa proposta apoia diretamente políticas de provisionamento de recursos cientes da Qualidade de Serviço (QoS). A metodologia proposta foi validada através de aplicações com características distintas: uma aplicação científica para o auxílio do diagnóstico de doenças pulmonares e uma aplicação Web que emula um site de leilões. Os modelos de desempenho computacional gerados foram confrontados com os dados reais através de métodos estatísticos gráficos e analíticos a fim de avaliar sua acurácia e todos os modelos apresentaram um percentual de erro inferior a 10%. A modelagem proposta para o controlador preditivo mostrou-se efetiva pois foi capaz de dinamicamente manter o tempo de resposta próximo ao valor esperado, com erro percentual absoluto médio (MAPE ) = 4.36% sem violação de SLA.

Threat perception is an important issue in today's world. As the line between hostile and non-hostile entities is blurred, it becomes more important for individuals to clearly distinguish between those who would present danger and those who would not. This series of experiments tested whether observers engaged in a dual-task paradigm perceived a greater amount of threat from target stimuli than they did when they were engaged in the threat task alone. The first experiment revealed that observers rated targets as more threatening when they were engaged in the additional task than when they only rated the targets themselves. Response time to the targets was also slower when a secondary task was present. This difference was more pronounced when the secondary task was presented via the auditory channel. Participants also rated overall workload higher when performing a secondary task, with the highest ratings being associated with the dual-task auditory condition. In the second experiment, the design crossed sensory modality with the presence or non-presence of threat. Inter-stimulus interval was also manipulated. The presence of threat was associated with faster response times, though when both tasks had threat components, response time was not the fastest. Additionally, when images came first in the stimulus pairs, observers were slower to respond to the first stimulus than when the sounds were presented first. Results supported the conclusion that additional task loading can affect the perception of threat. The modality of the additional task seems to also play a role in threat assessment performance. Results also led to the conclusion that threat-related visual stimuli are more challenging to process than threat-related auditory stimuli. Future research can now investigate how different types of tasks affect the threat perception task. Implications for better training of soldiers and for the design of automated systems are presented.
Ph.D.
Department of Psychology
Sciences
Psychology

Aversion is a complex phenomenon that arises over time through performance of cognitively demanding tasks and has been associated with the mechanisms of mental fatigue and compensatory control. However, little is known about this sensation to dissociate from the task at hand and the causation thereof. It is apparent that aversion is a negative state for the operator and could result in decreased performance and productivity. Through identification of factors that contribute to aversion when performing cognitively demanding tasks, recommendations to reduce design deficits may be employed to promote worker wellbeing and further advance performance and productivity. The current study examined possible factors that may influence aversion experienced through execution of cognitive tasks. A subsequent aim of this study was to assess a possible cause of aversion. The cause of aversion was hypothesized to be related to efficiency, namely the perception of efficiency when performing tasks and actual efficiency calculated through performance of tasks in relation to the expenditure of effort. Four investigations were undertaken with a non-repeated design between investigations and a repeated design within investigations. The first investigation was an analysis of the effect that stimulus cycling had on the aversion experienced. This consisted of a proof reading task with two conditions varying in the repetitiveness of the text, therefore, allowing an analysis as to how aversion is altered by the provision of a new stimulus to the participants. Investigation two investigated the effect that task difficulty imposed on aversion experienced. This comprised of two conditions with varied difficulty that were implemented through a driving simulator tracking task with difficulty altered by the width of the driving lane. The effect of performance feedback on the aversion experienced towards a task was the focus of the third investigation. The effect on aversion experienced was assessed through a driving simulator tracking task with a condition providing feedback of performance to participants and a condition with no knowledge of performance. The final experiment evaluated the effect of task alternations on aversion. This experiment was conducted through alternations between a driving simulator tracking task and a choice reaction task. The choice reaction tasks required participants to identify critical and non-critical stimulus. Four conditions were required for this experiment and were made up of two conditions where there was provision of alternation that varied in frequencies between the two tasks (medium alternation condition and fast alternation condition) and two conditions where no alternations were instated (driving simulator task condition and choice reaction task condition). Separations between all testing conditions were three or more days apart with sixty participants distributed between the investigations. Test duration of each condition was 30 minutes. Subjective data was recorded throughout investigations for all conditions in the form of aversion, subjectively perceived efficiency and rate of perceived exertion. Objective data was collected in the form of physiological responses and performance of tasks for the analysis of objective efficiency. For factors influencing aversion analysis, no differences in aversion experienced were found for the task difficulty and performance feedback investigations. Aversion was found to be less for the changes imposed through the task cycles and task alternation investigations. This concludes that aversion is aggravated through monotonous tasks and by a change of the stimulus or the structure of the cognitive tasks provided to operators; aversion can be alleviated. The results for the cause of aversion analysis found no difference in objective efficiency over time, with a subsequent decrease in perceived efficiency associated with the increasing aversion. Inference from these findings suggest that aversion cannot be attributed to objective inefficiency of task performance, however it can further be assumed that perception of actual efficiency is inaccurate. Perception of efficiency however had a large influence on the sensation of aversion. Aversion is seen to be more of a product of time on task, however whether this is mechanism of fatigue or compensatory control is still to be determined.

Despite extensive research into the concept of mental fatigue there is as yet no “gold standard” definition or measurement technique available. Because of this a large amount of fatigue-related errors are still seen in the workplace. The complexity of the problem lies with the inability to directly measure mental processes as well as the various endogenous and exogenous factors that interact to produce the experienced fatigue. Fatigue has been divided into sleep-related and task-related fatigue; however the task-related aspect is evident both during normal waking hours as well as during periods of sleep deprivation, therefore this aspect is considered important in the understanding of fatigue in general. The concept of task-related fatigue has further been divided into active and passive fatigue states; however differentiation between the two requires careful consideration. Various physiological measures have been employed in an attempt to gain a better understanding of the mechanisms involved in the generation of fatigue, however often studies have produced dissociating results. The current study considered the task-related fatigue elicited by a tracking task requiring sustained attention, in order to evaluate the usefulness of various cardiovascular and oculomotor measures as indicators of fatigue. A secondary aim was to determine whether the behavioural and physiological parameter responses could be used to infer the type of fatigue incurred (i.e. an active versus passive fatigue state) as well as the energetical mechanisms involved during task performance. A simple driving simulator task was used as the main tracking task, requiring constant attention and concentration. This task was performed for approximately two hours. Three experimental groups (consisting of 14 subjects each) were used: a control group that performed the tracking task only, a group that performed a five minute auditory memory span task concurrently with the driving task after every 20 minutes of pure driving, and a group that performed a visual choice reaction task for five minutes following every 20 minute driving period. The secondary tasks were employed in order to evaluate the extent of resource allocation as well as arousal level. Performance measures included various driving performance parameters, as well as secondary task performance. Physiological measures included heart rate frequency (HR) and various time- and frequency-domain heart rate variability (HRV)parameters, pupil dilation, blink frequency and duration, fixations, and saccadic parameters as well as critical flicker fusion frequency (CFFF). The Borg CR-10 scale was used to evaluate subjective fatigue during the task, and the NASA-TLX was completed following the task. A decline in driving performance over time was supplemented by measures such as HR, HRV and pupil dilation indicating an increase in parasympathetic activity (or a reduction in arousal). An increase in blink frequency was considered as a sign of withdrawal of attentional resources over time. Longer and faster saccades were also evident over time, coupled with shorter fixations. With regards to the secondary task influence, the choice RT task did not affect any behavioural or physiological parameters, thereby contesting the active fatigue theory of resource depletion, as well as implying that the increase in demand for the same resources used by the primary task was insufficient to affect the state of the subjects. The increased load elicited by the memory span task improved driving performance and increased measures of HR, HRV, pupil dilation and blink frequency. Some of these measures produced opposite effects to what was expected; an attempt to explain the dissociation of the various physiological parameters was expressed in terms of arousal, effort and resource theories. Overall, the results indicate that the fatigue and/or reduced arousal accompanying a monotonous sustained attention task can, to some degree, be alleviated through intermittent performance of a secondary task engaging mental resources other than the ones used for the primary task. The degree to which such a task is beneficial, however, requires careful consideration as while an immediate increase in arousal and primary task performance is noted, the impact of the task on general attentional resources may be detrimental in the case of reacting should an emergency situation occur.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 92-94).
Beth Israel Deaconess Medical Center (BIDMC) has partnered with the Gordon and Betty Moore Foundation's to eliminate preventable harm in the Intensive Care Unit (ICU). Many medical publications suggest nursing workload as a major contributor to patient safety. However, BIDMC was not using any tool to measure nursing workload, and as a result, nurse staffing decisions were made solely based on the ad hoc judgment of senior nurses. The objective of this thesis is to create a prospective nursing workload measurement and ultimately use it to improve staffing decisions in ICUs. To create a nursing workload measurement, a wildly-adopted patient-based scoring system, the Therapeutic Intervention Score System (TISS), was modified to BIDMC's ICUs. With consultation from clinicians and nurses, changes were made to the TISS to reflect BIDMC's workflow, and a new nursing workload scoring system called the Nursing Intensity Score (NIS) was created. The NIS for each patient per shift was calculated over a two-year period to gain further insights to improve staffing decisions. After looking at the current state, there was no correlation between nursing staffing and overall patient workload in the unit. In addition, nurses with 1 patient (1:1 nurses) had significantly less workload than nurses with two patients (1:2 nurses) even though they were expected to be the same. Finally, there was one overworked nurse (150% of median nursing workload) in every three shifts in the ICU. A prospective approach to analyze patient workload was developed by dividing patients based on clinical conditions and categorizing the results on two axis: the nominal workload level and the variability around the nominal value of workload. This analysis suggests that, a majority of patients are predictable, including a few patients with high but predictable load. On the other hand, some patients are highly unpredictable. A nursing backup system was proposed to balance workload between 1:1 and 1:2 nurses. To test the proposal, a simulation was developed to model the ICU with the goal of minimizing the number of overworked nurses. The best backup system was a buddy pairing system based on predictive model of patient conditions, with the resource nurse as the ultimate backup.
by Yiyin Ma.
M.B.A.
S.M.

This thesis measured the mental workload associated with operating a voice activated software application run on wearable computer under five different communication styles (buttons, command line, icon buttons, icon text menus, and text menus). The goal of this thesis was to determine which communication style would be best allow wearable computer users to simultaneously perform other non-computer tasks. Thirty subjects were randomly assigned to using one of five software versions (n = 6), each of which utilized a unique communication style. The mental workload associated with operating each version was assessed by monitoring the performance of secondary tasks. Secondary tasks consisted of completing a block assembly, digit subtraction, and walking along a marked pathway. Each secondary task was performed twice by itself and once while operating one of the software versions, creating a total of nine trials per subject. Block assembly task performance measures included average assembly time, percentage correct blocks, and percentage correct blocks attempted. Digit subtraction measures included percentage of correct digits. And path walking measures included average walking speed. Subjective estimates of mental workload were also collected for those trials in which subjects operated the wearable computer and performed physical tasks using the NASA Task Load Index (TLX). Finally, usability information was collected for each software version via a questionnaire form. Each of the five versions of the experimental software application was operationally identical to the others, but utilized a separate communication style. The button version displayed available functions via sets of labeled buttons in the control screen. The icon button version replaced the appearance of these buttons with labeled icons. The text menu version displayed available functions textually via a pull down main menu. The icon text version displayed appended icons to the left of each main menu item. Finally, the command line version displayed no labels, buttons, menus, or icons for any functions. The experimental software was designed as a day planner/scheduling application used to set reminder dates on a calendar, edit task lists, and edit phone listings. Under the multiple resource view of mental workload, it was hypothesized that the different versions and secondary tasks would demand distinct types of mental resource and, consequently, that mental workload would be observed as lowest when the version and secondary task demanded different types of mental resources. In contrast, it was also hypothesized that mental workload would be observed as highest when the version and secondary task demanded the same type of mental resources. Although separate one way ANOVAs performed on all secondary task measures failed to indicate statistically significant differences in mental workload across the versions, secondary task performance was consistently observed as best for subjects using the icon button version. Analysis of NASA TLX subscale data indicated that the block assembly task was rated as requiring less effort and the digit task rated as requiring less mental demand when the icon button version was used. These results generally support using an icon button communication style for wearable computer software applications. Results of this study are applicable to the design of the user interface of wearable computers. These results not only report subjective and objective measures for assessing the amount of mental effort associated with operating a wearable computer and performing various physical tasks simultaneously, but also provide estimates for determining the amount of physical task performance decrement to expect when wearable computer are also operated. Such data may be used to determine human factors guidelines for matching wearable computer interfaces to physical tasks so that interference between the two is minimal.
Master of Science

Workers are challenged by the increasingly complex multitasking environments they experience. To interact effectively with these environments, they must avoid overload. When workers get overloaded (when their mental demands exceed the resource capacity) quality drops, performance degrades, and safety suffers. What is largely unknown, however, is whether these results translate to postural tasks. Postural stability exhibits an entirely different set of challenges: injury, the danger of slips and falls, and risks associated with aging workers or those who have mental or physical challenges. An assembly line worker, for example, must assume different postures, interact with the product in some way, and react to visual and auditory alarms. Mistakes could be dangerous. It is clearly important, then, to understand the interactive effects of mental and postural workload. The goal of this research was to quantify the effects of mental and postural demands on overall workload. To accomplish this, we implemented three studies that were designed to capture the synergistic effects of different task types on overall workload and compare different types of workload measures against each other to help further design research in the area. We designed a dual-task mental/postural protocol to test the differential effects of a series of cognitive demands found in dual-task postural studied. The results of the first study depict a clear picture: the addition of an auditory task to unstable seating decreases postural sway. Based solely on this result, it might be concluded that workload did not increase. Using the same protocol while measuring mental workload however, we found that workload did in fact increase both subjectively and objectively, even when similar postural benefit was found. Even as performance seemed to improve, the participant moved nearer to possible overload and performance decrement (a condition we did not induce in this research). Based on the differences found between the different measures, we believe the importance of measuring overall workload as well as individual task performance in cognitive/postural dual-task research is very high.
Ph. D.

The requirements for real-time systems in safety-critical applications typically contain strict timing constraints. The design of such a system must be subject to extensive validation to guarantee that critical timing constraints will never be violated while the system operates. A mathematically rigorous technique to do so is to perform a schedulability analysis for formally verifying models of the computational workload. Different workload models allow to describe task activations at different levels of expressiveness, ranging from traditional periodic models to sophisticated graph-based ones. An inherent conflict arises between the expressiveness and analysis efficiency of task models. The more expressive a task model is, the more accurately it can describe a system design, reducing over-approximations and thus minimizing wasteful over-provisioning of system resources. However, more expressiveness implies higher computational complexity of corresponding analysis methods. Consequently, an ideal model provides the highest possible expressiveness for which efficient exact analysis methods exist. This thesis investigates the trade-off between expressiveness and analysis efficiency. A new digraph-based task model is introduced, which generalizes all previously proposed models that can be analyzed in pseudo-polynomial time without using any analysis-specific over-approximations. We develop methods allowing to efficiently analyze variants of the model despite their strictly increased expressiveness. A key contribution is the notion of path abstraction which enables efficient graph traversal algorithms. We demonstrate tractability borderlines for different classes of schedulers, namely static priority and earliest-deadline first schedulers, by establishing hardness results. These hardness proofs provide insights about the inherent complexity of developing efficient analysis methods and indicate fundamental difficulties of the considered schedulability problems. Finally, we develop a novel abstraction refinement scheme to cope with combinatorial explosion and apply it to schedulability and response-time analysis problems. All methods presented in this thesis are extensively evaluated, demonstrating practical applicability.

The objective of the present study was to investigate and compare the human responses to two load carriage tasks performed with three different load masses and on three different gradients. The task of carrying hydrogel in one hand was observed in a silviculture industry and crude physiological and perceptual responses were measured. This task was simulated in a laboratory setting together with a suggested intervention of backpack carriage. Eighteen conditions were established which consisted of the two modes of carriage and a combination of three load masses (9kg, 12kg and 15kg) and three gradients (5%, 10% and 15%). Twenty eight Rhodes University female students comprised the sample and the experimental procedures were conducted on a Quinton treadmill. Each participant was required to complete nine of the eighteen conditions which were each four minutes in duration. Postural changes were assessed using lateral and posterior digital images taken at the second and fourth minute and compression and shearing forces were estimated with the ErgolmagerTM Physiological responses (heart rate, ventilation and metabolic responses) were measured continuously with the Quark b² and perceptual responses ('central' and 'local' RPE) were measured every minute during the experimentation and body discomfort was rated at the completion of each condition. Overall responses revealed that hand carriage (146 bt.min⁻¹ , 25.09 mIO₂. kg-l.min⁻¹) was generally found to be more physiologically stressful than backpack carriage (130 bt.min⁻¹, 22.15 mIO₂.kg⁻¹ .min⁻¹) independent of load mass and gradient. Physiological responses were higher (113 bt.min-1 to 174 bt.min⁻¹ ) in responses to increasing gradient as opposed to increasing load mass (104 bt.min-1 to 153 bt.min⁻¹ ) for both backpack and hand carriage. Categorisation using the guidelines of Sanders and McCormick (1993) allowed for classification of conditions, with respect to physiological responses, into 'moderate', 'heavy' and 'very heavy' stress. For almost all of the physiological responses the majority of conditions which were classified as 'moderate' were backpack carriage conditions and the conditions classified as 'very heavy' were mostly hand carriage conditions. In terms of postural responses hand carriage resulted in more strain and greater compression and shearing forces on the spine. In terms of the compression forces increasing gradient had a greater affect on backpack carriage (681 N to 935 N) compared to hand carriage (570N to 793N). In contrast, increasing load mass had a larger affect on hand carriage postures and compression forces (751 N to 935N) in comparison to backpack carriage (723N to 780N). Shearing forces were found to be worse in hand carriage conditions overall. Although participants generally underrated perceived exertion in relation to cardiorespiratory responses, these perceptions revealed that backpack carriage, with a mean 'central' RPE of 12 compared to 11 for hand carriage, was somewhat preferred to hand carriage and that increasing gradient was perceived to be marginally more straining than increasing load mass.

With the current high rate of development and deployment of Remotely Piloted Aerial Systems (RPAS) for both commercial and military sectors globally, it is key to understand the implications this technology has on current and future RPAS operators and the consequential effect on licensing, training and performance measurement. This thesis investigates aspects of training and potential objective performance measurement of RPAS operators, this is carried out by reviewing current literature relating to RPAS and associated human factors thus a gap analysis was undertaken and a set of experiments/evaluations were devised to provide important new insights. Attention is drawn to the type of skill set required for future RPAS operations. A factor has been to understand whether a regular computer games player displays differing simulator interaction, in this case information gathering and analysis patterns, to that of someone with limited to no computer games experience. To achieve the aims of the research experimentation had to be carried which required the development of an appropriate simulator followed by the inclusion of a case study and the creation of bespoke performance data analysis software, SimPACT. Although performance differentials have been observed through action it was hoped to be able to identify performance differential characteristics through the means of evaluating the use of disparate physical data sets; the research, in fact, identified no significant difference between data set use and it must be concluded that any pre-action performance differential cannot be measured, at least not with the equipment available. However computer gamers, rather than having differing information acquisition strategies, have differing and more effective information retention and processing pathways likely to have been developed through continuous gaming which can be applied to any game-type environment and, potentially, any type of interactive task. These results have been proven to be statistically viable and observable. This research has contributed to the understanding of human performance measurement within the RPAS sector, including the addition of new data processing software, as well as provide new evidence relating to difference within human data gathering and processing between groups of differing experiences.

With the development of technology, people's viewpoints of the automobile have shifted; instead of merely a means of transportation, the automobile has become a space in which a driver can still perform daily activities besides driving, such as communicating with other people, interacting with electronic devices, and receiving information. In the meantime, different ways of interaction have been explored. Among all the modalities, gestures have been considered as a feasible way for performing in-car secondary tasks because of their intuitiveness. However, few researches have been conducted in terms of subjects' cognitive load. This thesis has examined four gesture interfaces (air swipe, air tap, screen swipe, and screen tap), in terms of their effects on drivers' driving performance, secondary task performance, perceived cognitive load, and eye glance behavior. The result demonstrated that air gestures are generally slower than screen gestures with regard to secondary performance. Screen swipe gesture requires the lowest cognitive load while air swipe and screen tap gesture remain the same. Subjects in this study tend to prefer screen swipe gesture the most while prefer air tap gesture the least. However, there is no significant difference between air swipe and screen tap gesture. Although air tap gesture and screen tap gesture generated the largest amount of dwell times, no variance among the four gesture interfaces in driving performance has been found. The result indicated that even though air gestures are not limited by space, screen swipe in this study still seemed to be the most ideal way for performing in-car secondary task of music selection.

Emerging architecture designs include tens of processing cores on a single chip die; it is believed that the number of cores will reach the hundreds in not so many years from now. However, most common workloads cannot expose fluctuating parallelism, insufficient to utilize such systems. The combination of these issues suggests that large-scale systems will be either multiprogrammed or have their unneeded resources powered off. To achieve these features, workloads must be able to provide a metric on their parallelism which the system can use to dynamically adapt per-application resource allotments.Adaptive resource management requires scheduling abstractions to be split into two cooperating layers. The system layer that is aware of the availability of resources and the application layer which can accurately and iteratively estimate the workload's true resource requirements.This thesis addresses these issues and provides a self-adapting work-stealing scheduling method that can achieve expected performance while conserving resources. This method is based on deterministic victim selection (DVS) that controls the concentration of the load among the worker threads. It allows to use the number of spawned but not yet processed tasks as a metric for the requirements. Because this metric measures work to be executed in the future instead of past behavior, DVS is versatile to handlevery irregular workloads.

QC 20130910

Although modeling and simulation are fertile areas for research and development within medicine, education, and human factors, there is a growing need for fully integrated organ systems as part of any digital human model (DHM). This need is particularly high in task-based survivability assessment. However, the current static geometry used in DHM is insufficient for evaluating conditions during simulated task performance. This insufficiency is due to the fact that internal viscera are inherently non-rigid objects. Therefore, undesirable, and unrealistic behaviors occur when using static models to represent internal viscera as the DHM moves through a variety of postures. The capacity for DHMs to take on a variety of postures and positions contributes to their overall usefulness in modeling and simulation. By using static models to represent internal viscera, errors in model behavior must be tolerated, or the DHM must be limited to a posture that matches the models’ configurations. With the either option being undesirable there is a need to represent internal viscera using dynamic models. A dynamic model will allow for the geometry used in representing the internal viscera to deform as the DHM. Thus this work proposes a computational platform for controlling the motion and deformation of internal viscera models within a DHM. This platform consists of two components. The first component is a new method for maintaining a relative position within a dynamic character’s mesh called skin-based parenting. The second component is a system which takes a free-from deformation technique used in artistic modeling and eliminates the manual input that is usually required. This platform produces representations of internal viscera which conform to the character’s posture in real-time at an interactive rate. Thus enabling the assessment of how particular environmental influences relate to the position and orientation of internal viscera models within a DHM in a variety of postures.

Human error taxonomies have been implemented in numerous safety critical industries. These taxonomies have provided invaluable insight into understanding the underlying causes of human error; however, their utility for actually predicting future errors remains in question. A need has been identified for another approach to supplement what we can extrapolate from taxonomies and better predict human error. Task network modeling is a promising approach to human error prediction that had yet to be empirically evaluated. This study tested a task network modeling approach to predicting human error in the context of automotive assembly. The task network modeling architecture was expanded to include a set of predictors from the human error literature, and used to model part of an operational automotive assembly plant. This manuscript contains three studies. Study 1 tested separate task network models for two different target areas of an active automotive assembly line. Study 2 tested the validity of predictions made by the models from Study 1, both within and across samples. Study 3 tested predictions across both models on a larger sample of vehicles. The expanded architecture accounted for 21.9% to 36.5% of the variance in human error and identified 12 explanatory variables that significantly predicted the occurrence of human error. Model outputs were used to compute prediction equations that were tested using binary logistic regression and then cross-validated twice using both split-half and cross-sample validation. The predictors of Time Pressure, Visual Workload, Auditory Workload, Cognitive Workload, Psychomotor Workload, Task Frequency, Information Flow, Teamwork, and Equipment Feedback were significant predictors of human error in all three models that were tested. The variables of Information Presentation and Task Dependency varied in significance across samples, but both were significant in two out of the three models. The variables of Shift and Hour into Shift were never significant in any of the three models. The variables that were greatly stable across studies were all related to the tasks being performed by each worker at each station. The variables related to the timing of errors, on the other hand, were never significant. The results indicate that an expanded task network architecture is a great tool for predicting the situations and circumstances in which human errors will occur, but not the timing of when they will occur. Nevertheless, task network modeling demonstrated to provide useful, valid, and accurate predictions of human error and should continue to be developed as an error prediction tool.

Unmanned aerial systems (UASs) often require multiple human operators fulfilling diverse roles for safe and correct operation. Reliably designing the human interaction, autonomy, and decision making aspects of these systems requires the use of modeling. We propose a conceptual model that models human machine interaction systems as a group of actors connected by a network of communication channels. We present a simulation framework implemented in Java, with an optional XML model parser that can be analyzed using the Java Pathfinder (JPF) model checker. We propose two human workload metrics based on a taxonomy extracted from the relevant literature. Using the simulator to produce a workload profile over time for each human actor, we conducted a case study by modeling a UAS integrated into the National Airspace System. Additionally we adapted an existing cognitive workload metric to act as a baseline. The results of this case study were consistent with known workload events and the results of our baseline metric.

This thesis studies cloud capacity auto-scaling, or how to provision and release re-sources to a service running in the cloud based on its actual demand using an auto-matic controller. As the performance of server systems depends on the system design,the system implementation, and the workloads the system is subjected to, we focuson these aspects with respect to designing auto-scaling algorithms. Towards this goal,we design and implement two auto-scaling algorithms for cloud infrastructures. Thealgorithms predict the future load for an application running in the cloud. We discussthe different approaches to designing an auto-scaler combining reactive and proactivecontrol methods, and to be able to handle long running requests, e.g., tasks runningfor longer than the actuation interval, in a cloud. We compare the performance ofour algorithms with state-of-the-art auto-scalers and evaluate the controllers’ perfor-mance with a set of workloads. As any controller is designed with an assumptionon the operating conditions and system dynamics, the performance of an auto-scalervaries with different workloads.In order to better understand the workload dynamics and evolution, we analyze a6-years long workload trace of the sixth most popular Internet website. In addition,we analyze a workload from one of the largest Video-on-Demand streaming servicesin Sweden. We discuss the popularity of objects served by the two services, the spikesin the two workloads, and the invariants in the workloads. We also introduce, a mea-sure for the disorder in a workload, i.e., the amount of burstiness. The measure isbased on Sample Entropy, an empirical statistic used in biomedical signal processingto characterize biomedical signals. The introduced measure can be used to charac-terize the workloads based on their burstiness profiles. We compare our introducedmeasure with the literature on quantifying burstiness in a server workload, and showthe advantages of our introduced measure.To better understand the tradeoffs between using different auto-scalers with differ-ent workloads, we design a framework to compare auto-scalers and give probabilisticguarantees on the performance in worst-case scenarios. Using different evaluation cri-teria and more than 700 workload traces, we compare six state-of-the-art auto-scalersthat we believe represent the development of the field in the past 8 years. Knowingthat the auto-scalers’ performance depends on the workloads, we design a workloadanalysis and classification tool that assigns a workload to its most suitable elasticitycontroller out of a set of implemented controllers. The tool has two main components;an analyzer, and a classifier. The analyzer analyzes a workload and feeds the analysisresults to the classifier. The classifier assigns a workload to the most suitable elasticitycontroller based on the workload characteristics and a set of predefined business levelobjectives. The tool is evaluated with a set of collected real workloads, and a set ofgenerated synthetic workloads. Our evaluation results shows that the tool can help acloud provider to improve the QoS provided to the customers.

Emerging architecture designs include tens of processing cores on a single chip die; it is believed that the number of cores will reach the hundreds in not so many years from now. However, most common parallel workloads cannot fully utilize such systems. They expose fluctuating parallelism, and do not scale up indefinitely as there is usually a point after which synchronization costs outweigh the gains of parallelism. The combination of these issues suggests that large-scale systems will be either multiprogrammed or have their unneeded resources powered off.Multiprogramming leads to hardware resource contention and as a result application performance degradation, even when there are enough resources, due to negative share effects and increased bus traffic. Most often this degradation is quite unbalanced between co-runners, as some applications dominate the hardware over others. Current Operating Systems blindly provide applications with access to as many resources they ask for. This leads to over-committing the system with too many threads, memory contention and increased bus traffic. Due to the inability of the application to have any insight on system-wide resource demands, most parallel workloads will create as many threads as there are available cores. If every co-running application does the same, the system ends up with threads $N$ times the amount of cores. Threads then need to time-share cores, so the continuous context-switching and cache line evictions generate considerable overhead.This thesis proposes a novel solution across all software layers that achieves throughput optimization and uniform performance degradation of co-running applications. Through a novel fully automated approach (DVS and Palirria), task-parallel applications can accurately quantify their available parallelism online, generating a meaningful metric as parallelism feedback to the Operating System. A second component in the Operating System scheduler (Pond) uses such feedback from all co-runners to effectively partition available resources.The proposed two-level scheduling scheme ultimately achieves having each co-runner degrade its performance by the same factor, relative to how it would execute with unrestricted isolated access to the same hardware. We call this fair scheduling, departing from the traditional notion of equal opportunity which causes uneven degradation, with some experiments showing at least one application degrading its performance 10 times less than its co-runners.

QC 20151016

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 151-156).
Currently, numerous automated systems need constant monitoring but require little to no operator interaction for prolonged periods, such as unmanned aerial systems, nuclear power plants, and air traffic management systems. This combination can potentially lower operators' workload to dangerously low levels, causing boredom, lack of vigilance, fatigue, and performance decrements. As more systems are automated and placed under human supervision, this problem will become more prevalent in the future. To mitigate the problem through predicting operator performance in low task load supervisory domains, a queuing-based discrete event simulation model has been developed. To test the validity and robustness of this model, a testbed for single operator decentralized control of unmanned vehicles was utilized, simulating a low workload human supervisory control (HSC) environment. Using this testbed, operators engaged in a four-hour mission to search, track, and destroy simulated targets. Also, a design intervention in the form of cyclical auditory alerts was implemented to help operators sustain directed attention during low task load environments. The results indicate that the model is able to accurately predict operators' workload. Also, the model predicts operators' performance reasonably well. However, the inability of the model to account for operator error is a limiting factor that lowers model's accuracy. The results also show that the design intervention is not useful for operators who do not have difficulties sustaining attention for prolonged periods. The participants of this study were exceptional performers, since most of them had very high performance scores. Further research will investigate the possibility of conducting another low task load, long duration study with a more diverse set of participants to assess the impact of the design intervention and to extract personality traits that may affect system performance. Also, the model needs to be revised to take into account operator errors, which can significantly affect performance of HSC systems.
by Armen A. Mkrtchyan.
S.M.

The purpose of this research was to examine operator workload and performance in a high risk, multi-task environment. Specifically, the research examined if a gunner of a Future Combat System, such as a Mounted Combat System, could effectively detect targets in the immediate environment while concurrently operating robotic assets in a remote environment. It also analyzed possible effects of individual difference factors, such as spatial ability and attentional control, on operator performance and workload. The experimental conditions included a gunner baseline and concurrent task conditions where participants simultaneously performed gunnery tasks and one of the following tasks: monitor an unmanned ground vehicle (UGV) via a video feed (Monitor), manage a semi-autonomous UGV, and teleoperate a UGV (Teleop). The analysis showed that the asset condition significantly impacted gunnery performance with the gunner baseline having the highest number of targets detected (M = 13.600 , SD = 2.353), and concurrent Teleop condition the lowest (M = 9.325 , SD = 2.424). The research also found that high spatial ability participants tended to detect more targets than low spatial ability participants. Robotic task performance was also affect by the asset condition. The results showed that the robotic target detection rate was lower for the concurrent task conditions. A significant difference was seen between the UGV-baseline (80.1%) when participants performed UGV tasks only and UGV-concurrent conditions (67.5%) when the participants performed UGV tasks concurrently with gunnery tasks. Overall, this study revealed that there were performance decrements for the gunnery tasks as well as the robotic tasks when the tasks were performed concurrently.
M.S.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering and Management Systems

In human-computer systems, such as supervisory control systems, large volumes of incoming and complex information can degrade overall system performance. Strategically integrating automation to offload tasks from the operator has been shown to increase not only human performance but also operator efficiency and safety. However, increased automation allows for increased task complexity, which can lead to high cognitive workload and degradation of situational awareness. Adaptive automation is one potential solution to resolve these issues, while maintaining the benefits of traditional automation. Adaptive automation occurs dynamically, with the quantity of automated tasks changing in real-time to meet performance or workload goals. While numerous studies evaluate the relative performance of manual and adaptive systems, little attention has focused on the implications of selecting particular invoking or revoking strategies for adaptive automation. Thus, evaluations of adaptive systems tend to focus on the relative performance among multiple systems rather than the relative performance within a system. This study takes an intra-system approach specifically evaluating the relationship between cognitive workload and situational awareness that occurs when selecting a particular invoking-revoking strategy for an adaptive system. The case scenario is a human supervisory control situation that involves a system operator who receives and interprets intelligence outputs from multiple unmanned assets, and then identifies and reports potential threats and changes in the environment. In order to investigate this relationship between workload and situational awareness, discrete event simulation (DES) is used. DES is a standard technique in the analysis of systems, and the advantage of using DES to explore this relationship is that it can represent a human-computer system as the state of the system evolves over time. Furthermore, and most importantly, a well-designed DES model can represent the human operators, the tasks to be performed, and the cognitive demands placed on the operators. In addition to evaluating the cognitive workload to situational awareness tradeoff, this research demonstrates that DES can quite effectively model and predict human cognitive workload, specifically for system evaluation. This research finds that the predicted workload of the DES models highly correlates with well-established subjective measures and is more predictive of cognitive workload than numerous physiological measures. This research then uses the validated DES models to explore and predict the cognitive workload impacts of adaptive automation through various invoking and revoking strategies. The study provides insights into the workload-situational awareness tradeoffs that occur when selecting particular invoking and revoking strategies. First, in order to establish an appropriate target workload range, it is necessary to account for both performance goals and the portion of the workload-performance curve for the task in question. Second, establishing an invoking threshold may require a tradeoff between workload and situational awareness, which is influenced by the task's location on the workload-situational awareness continuum. Finally, this study finds that revoking strategies differ in their ability to achieve workload and situational awareness goals. For the case scenario examined, revoking strategies based on duration are best suited to improve workload, while revoking strategies based on revoking thresholds are better for maintaining situational awareness.
Ph.D.
Doctorate
Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering

The effects of in-vehicle automation and driving assistant systems on the mental workload and situation awareness of drivers have been the interest of many studies; some of the implications of automation in such man-machine systems have been identified. Due to the introduction of advanced automated systems in agricultural machinery, farmers are currently working with semi-autonomous vehicles. A human factors perspective on the design of these systems will ensure safe and efficient operation of such man-machine systems. In this study, a systematic approach was utilized to address human factors issues associated with operating a semi-autonomous agricultural vehicle, and to provide design recommendations. The study was carried out in three stages. First, a task analysis was used to identify tasks associated with operating an agricultural vehicle and to select appropriate experimental variables. Next, a preliminary experiment was performed to validate the test procedure and measurement techniques. Finally, the main experiment was administered. Experiments were conducted using the Tractor Driving Simulator located in the Agricultural Ergonomics Laboratory at the University of Manitoba. Thirty young experienced tractor drivers participated in this study. The experiment investigated the effects of i) vehicle steering task automation (VSTA) and ii) implement control and monitoring task automation (ICMTA) on mental workload and situation awareness of drivers. It was found that ICMTA significantly affected situation awareness (and its underlying components) of the operator. The situation awareness of drivers increased as the automation support level increased, but the highest level of automation, where the participants were out of the task loop, resulted in low situation awareness, similar to the condition with no automation support. VSTA only reduced the attentional demand of the situation, one of the three components of the situation awareness, which had negative effect on overall situation awareness. Based on the results from a subjective mental workload measure, moderate levels of mental workload were reported when the participants were involved in the implement control and monitoring task loop. The highest level of ICMTA reduced the average mental workload by 18%. Reaction time of drivers and number of errors committed by drivers both decreased as the automation level increased.
October 2015

Since the analysis of dynamics of intervals of short cardiovascular signals reflects important vital processes, involving complex interactions of the regulatory processes (Batzel, Bachar, 2010), mathematical formalism is one of the ways to research the complexity of biological systems (Davis et al., 2010). Concerning the interaction of various physiological systems / parameters that point out the causes of fatigue, the theory of non-linear dynamical systems enables to reveal this phenomenon as a part of dynamic system’s processes. Cardiovascular functional values are integral indicators, i.e. the values of the recorded parameters are affected by numerous factors or at least some of them. The question to which we tried to find the answer performing the following analysis of the data could be worded as follows. Apparently, the evaluation of the dynamic concatenation among these cardiovascular parameters, when the functional state of the subject changes, can reveal an increase or decrease in the significance of the selected structural component during the developing and incremental fatigue. The aim of the study was to find out the peculiarities in concatenation between central and peripheral cardiovascular indices under the conditions of increasing fatigue. Objectives: 1. To compare the peculiarities of dynamics in cardiovascular functional and functional state indices while performing increamental exercise up to inability by applying the provocative or increasing workload... [to full text]
Nauji tyrimų rezultatų analizės metodai, nauja tyrimų metodologija išplečia fiziologų galimybes pažinti naujas, ligi šiol neatskleistas organizmo funkcijų ypatybes, panaudoti jas funkcinei būklei vertinti, valdant fizinio ir kitokio poveikio trukmę, stiprumą, ieškant optimalaus poveikio ir adaptacijos efekto. Kompleksiškumo ypatybėms vertinti Lietuvos mokslininkai pasiūlė dinaminių sąsajų vertinimo metodiką, taikant algebrinį duomenų kointegracijos metodą (Navickas ir kt., 2005; Navickas, Bikulčienė, 2008; Vainoras et al., 2008; Bikulčienė et al., 2009; Poderys et al., 2010). Darbo tikslas – nustatyti aktyvių raumenų kraujotakos ir kitų ŠKS funkcinių rodiklių dinaminių sąsajų ypatybes atliekant didėjantį fizinį krūvį iki negalėjimo. Uždaviniai: 1. Palyginti ŠKS funkcinių ir funkcinės būklės rodiklių kaitos ypatybes atliekant pakopomis didėjantį fizinį krūvį iki negalėjimo, taikant provokacinio ir darbinio fizinio krūvio didinimo protokolus. 2. Nustatyti reikšmingų širdies ir kraujagyslių sistemos funkcinių rodiklių dinaminių sąsajų ypatybes veloergometru atliekant pakopomis didėjantį fizinį krūvį iki negalėjimo. 3. Nustatyti adaptacijos greitumo, arba ištvermės fiziniams krūviams, įtaką širdies ir kraujagyslių sistemos funkcinių rodiklių dinaminių sąsajų kaitai atliekant pakopomis didėjantį fizinį krūvį iki negalėjimo. 4. Nustatyti, ar galima algebriniu duomenų kointegracijos metodu gauti fiziologijai reikšmingą informaciją, vertinant dinamines sąsajas tarp rodiklių, kai... [toliau žr. visą tekstą]

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Defining accurate representations of group behaviors in simulations is an expensive, time-consuming task. One reason for this is that previously produced behaviors are often not reusable within other scenarios or simulations. Using Hierarchical Task Networks (HTNs) to model military behaviors is a promising technique for addressing this problem. HTNs provide a methodology for linking tactical behaviors, and offer a potential system for representing the military decision-making process at the tactical level. This thesis investigates the use of HTNs within the COMBATXXI model. COMBATXXI provides military planners a detailed representation of combat operations, and supports analysis efforts by providing insights into the effectiveness of weapon systems, unit organizations, and tactics. The use of HTNs within COMBATXXI is a relatively new concept; many aspects of HTN implementation have not been researched in depth. Work in this thesis involved development and testing of HTNs capable of executing a security formation behavior, and coordinating the execution of other ground combat related behaviors. The HTN-controlled behaviors were demonstrated in a simulated version of a United States Marine Corps live fire training range. The composable and dynamic aspects of these behaviors eased the scenario development process and added tactical realism to the test scenario.

Stroke survivors suffering from cognitive deficits experience difficulty completing their daily self-care activities. The latter are referred to as activities of daily living (ADL). The resulting loss of independence makes them rely on caregivers to help them go through their daily routine. However, such reliance on caregivers may conflict with their need for privacy and willingness to keep a control over their life. A possible solution to tackle this issue is the development of an assistive or rehabilitation system.

Driving under distraction may lead drivers to wrong actions that can result in serious accidents. The objective of this thesis was to apply a driving simulator to verify variations in drivers\' behavior while driving. Behavior to drive on a curve was measured by variation in drivers\' speed profile in a virtualized highway. The comparison was performed between two identical simulations, one involving drivers distracted with a mental workload, and other in which they were full aware of driving task. 54 volunteer drivers took part in this study, which was divided into 4 stages. 17 drivers performed the distraction test known as PASAT, and results showed that distracted drivers did not recognize the beginning of the curve and drove through it at speeds higher than those when they were fully aware. Moreover, driving performance was increased when drivers were aware of driving, thereby hitting high speeds in tangents, but perceiving curves in advance to reduce acceleration. This study confirms that driving simulators are beneficial in discovering drivers\' behavior exposed to activities that could be highly risky if driving in real situations.
A distração durante a atividade de direção pode levar o condutor de veículos automotores a cometer falhas, que podem ocasionar até mesmo acidentes graves. Este estudo aborda a utilização de simuladores de direção para verificar variações no comportamento de motoristas ao realizar a atividade de direção, distraídos ou com plena atenção na condução do veículo. O comportamento é medido pela variação no perfil de velocidade dos condutores para desenvolver uma curva considerada perigosa em uma rodovia simulada em ambiente virtual. A variação de velocidade deste perfil é comparada entre duas simulações idênticas, onde em uma delas os condutores estão distraídos com um teste que proporciona estresse mental e, na outra, estão com plena atenção à direção. 54 condutores fizeram parte deste estudo dividido em 3 etapas. 17 participantes realizaram o teste de distração conhecido como PASAT, e a análise dos resultados mostram que, distraídos, os condutores não perceberam o início da curva e desenvolveram velocidades maiores durante seu trajeto. Além disso, quando estavam com plena atenção à atividade de direção, o desempenho dos condutores foi melhor, atingindo velocidades maiores nas tangentes, mas percebendo as curvas antecipadamente e reduzindo suas velocidades antes de iniciar esses trechos.

In this thesis, we investigate methods by which discrete event network diffusion simulators may execute without the restriction of lockstep or near lockstep synchronicity. We develop a discrete event simulator that allows free clock drift between threads, develop a differential equations model to approximate communication cost of such a simulator, and propose an algorithm by which we leverage information gathered in the natural course of simulation to redistribute agents to parallel threads such that the burden of communication is lowered during future replicates.

Grasp should be selected intelligently to fulfill different stability properties and manipulative requirements. Currently, most grasping approaches consider only pick-and-place tasks without any physical interaction with other objects or the environment, which are common in an industry setting with limited uncertainty. When robots move to our daily-living environment and perform a broad range of tasks in an unstructured environment, all sorts of physical interactions will occur, which will result in random physical interactive wrenches: forces and torques on the tool. In addition, for a tool to perform a required task, certain motions need to occur. We call it "functional tool motion," which represents the innate function of the tool and the nature of the task. Grasping with a robotic hand gives flexibility in "mounting" the tool onto the robotic arm - a different grasp will connect the tool to the robotic arm with a different hand posture, then the inverse kinematics approach will result in a different joint motion of the arm in order to achieve the same functional tool motion. Thus, the grasp and the functional tool motion decide the manipulator's motion, as well as the effort to achieve the motion. Therefore, we propose to establish two objectives to serve the purpose of a grasp: the grasp should maintain a firm grip and withstand interactive wrenches on the tool during the task; and the grasp should enable the manipulator to carry out the task most efficiently with little motion effort, and then search for a grasp to optimize both objectives. For this purpose, two grasp criteria are presented to evaluate the grasp: the task wrench coverage criterion and the task motion effort criterion. The two grasp criteria are used as objective functions to search for the optimal grasp for grasp planning. To reduce the computational complexity of the search in high-dimensional robotic hand configuration space, we propose a novel grasp synthesis approach that integrates two human grasp strategies - grasp type, and thumb placement (position and direction) - into grasp planning. The grasping strategies abstracted from humans should meet two important criteria: they should reflect the demonstrator's intention, and they should be general enough to be used by various robotic hand models. Different abstractions of human grasp constrain the grasp synthesis and narrow down the solutions of grasp generation to different levels. If a strict constraint is imposed, such as defining all contact points of the fingers on the object, the strategy loses flexibility and becomes rarely achievable for a robotic hand with a different kinematic model. Thus, the choice of grasp strategies should balance the learned constraints and required flexibility to accommodate the difference between a human hand and a robotic hand. The human strategies of grasp type and thumb placement have such a balance while conveying important human intents to the robotic grasping. The proposed approach has been thoroughly evaluated both in simulation and on a real robotic system for multiple objects that would be encountered in daily living.

Crew coordination in the context of aviation is a specifically choreographed set of tasks performed by each pilot, defined for each phase of flight. Based on the constructs of effective Crew Resource Management and SOPs for each phase of flight, a shared understanding of crew workload and task responsibility is considered representative of well-coordinated crews. Nominal behavior is therefore defined by SOPs and CRM theory, detectable through pilot eye-scan. This research investigates the relationship between the eye-scan exhibited by each pilot and the level of coordination between crewmembers. Crew coordination was evaluated based on each pilot's understanding of the other crewmember's workload. By contrasting each pilot's workload-understanding, crew coordination was measured as the summed absolute difference of each pilot's understanding of the other crewmember's reported workload, resulting in a crew coordination index. The crew coordination index rates crew coordination on a scale ranging across Excellent, Good, Fair and Poor. Eye-scan behavior metrics were found to reliably identify a reduction in crew coordination. Additionally, crew coordination was successfully characterized by eye-scan behavior data using machine learning classification methods. Identifying eye-scan behaviors on the flight deck indicative of reduced crew coordination can be used to inform training programs and design enhanced avionics that improve the overall coordination between the crewmembers and the flight deck interface. Additionally, characterization of crew coordination can be used to develop methods to increase shared situation awareness and crew coordination to reduce operational and flight technical errors. Ultimately, the ability to reduce operational and flight technical errors made by pilot crews improves the safety of aviation.