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Добірка наукової літератури з теми "Workload"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 1 серпня 2024

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Статті в журналах з теми "Workload"

Hu, Bing, and Nicholas Mason. "Large scale analytics for workload segmentation." Journal of Management and Engineering Integration 16, no. 1 (June 2023): 19–26. http://dx.doi.org/10.62704/10057/25984.

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As the complexity and size of workload landscapes continue to evolve, traditional tools that are useful for characterizing workloads have gradually become inadequate. Approaches such as scaling studies or isolated analyses of a single workload are gradually becoming insufficient to understand the broad state of the workload universe. To address this problem, we follow a machine learning methodology to leverage large numbers of workload experiments that already exist on Intel. We advanced a workload analysis platform that stores, manages, and facilitates the analysis of workload information using two big data analysis software tools, a top-down workload decision classifier and a workload universe mapping tool, to characterize large-scale workloads. Both analysis tools present a novel way to look at workload data from a higher level and consider these new characteristics at the workload segmentation level. We seek to achieve this goal in alignment with the strategic goals of developing new benchmarks, informing market sizing, and detecting emerging workloads.

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Raza, Zahid, and Nupur Jangu. "Workload Classification." International Journal of Systems and Service-Oriented Engineering 12, no. 1 (January 2022): 1–14. http://dx.doi.org/10.4018/ijssoe.297135.

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Traditional cloud-only architecture faces the challenge of coexistence with the ever-increasing IoT devices and demands for the need of the hybrid cloud computing and fog/IoT architecture to realize better handling of workload/requests. Determining where the user-workload should be assigned depends on the workload itself, and thereby, the workload classification gains the pivotal role. This location and offloading decision to the right resource affects both users and the providers. This work describes various cloud-fog workloads and relates them to their suitable place of execution in such a hybrid environment. The workloads have been classified based on their different parameters and characteristics with the aim to identify appropriate resources for efficient resource provisioning. The workload classification and characterization promises a significant role in the resource management by efficient capacity planning, future resource requirement predictions, workload offloading and an improvement in the Quality of Service (QoS) leading to an improvement in the system performance.

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Malone, Shane, Mark Roe, Dominic A. Doran, Tim J. Gabbett, and Kieran D. Collins. "Protection Against Spikes in Workload With Aerobic Fitness and Playing Experience: The Role of the Acute:Chronic Workload Ratio on Injury Risk in Elite Gaelic Football." International Journal of Sports Physiology and Performance 12, no. 3 (March 2017): 393–401. http://dx.doi.org/10.1123/ijspp.2016-0090.

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Purpose:To examine the association between combined session rating of perceived exertion (RPE) workload measures and injury risk in elite Gaelic footballers.Methods:Thirty-seven elite Gaelic footballers (mean ± SD age 24.2 ± 2.9 y) from 1 elite squad were involved in a single-season study. Weekly workload (session RPE multiplied by duration) and all time-loss injuries (including subsequent-wk injuries) were recorded during the period. Rolling weekly sums and wk-to-wk changes in workload were measured, enabling the calculation of the acute:chronic workload ratio by dividing acute workload (ie, 1-weekly workload) by chronic workload (ie, rolling-average 4-weekly workload). Workload measures were then modeled against data for all injuries sustained using a logistic-regression model. Odds ratios (ORs) were reported against a reference group.Results:High 1-weekly workloads (≥2770 arbitrary units [AU], OR = 1.63–6.75) were associated with significantly higher risk of injury than in a low-training-load reference group (<1250 AU). When exposed to spikes in workload (acute:chronic workload ratio >1.5), players with 1 y experience had a higher risk of injury (OR = 2.22) and players with 2–3 (OR = 0.20) and 4–6 y (OR = 0.24) of experience had a lower risk of injury. Players with poorer aerobic fitness (estimated from a 1-km time trial) had a higher injury risk than those with higher aerobic fitness (OR = 1.50–2.50). An acute:chronic workload ratio of (≥2.0) demonstrated the greatest risk of injury.Conclusions:These findings highlight an increased risk of injury for elite Gaelic football players with high (>2.0) acute:chronic workload ratios and high weekly workloads. A high aerobic capacity and playing experience appears to offer injury protection against rapid changes in workload and high acute:chronic workload ratios. Moderate workloads, coupled with moderate to high changes in the acute:chronic workload ratio, appear to be protective for Gaelic football players.

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Simmons, Nadine C., and Suzanne S. Kuys. "Trial of an allied health workload allocation model." Australian Health Review 35, no. 2 (2011): 168. http://dx.doi.org/10.1071/ah09860.

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Allied health (AH) managers need to be able to quantify workloads to effectively manage the increasing demands on the health system. Workload allocation models provide a means of monitoring, evaluating and determining manageable workloads. This allows managers to ensure equitable distribution of duties and maximise the existing AH workforce output, which will lead to more efficient health service delivery and better patient outcomes. The purpose of this study was to develop and trial an AH workload allocation model incorporating the National Allied Health Casemix Committee Health Activity Classification. A workload allocation model was developed that included a staff workload mapping tool, data analysis spreadsheet and guidelines for calculating procedure times. The model was trialled across three AH professions (occupational therapy, physiotherapy and speech pathology), in two hospital districts, and across inpatient, outpatient and community settings. A total of 30 participants completed the trial. Staff and managers completed a post-trial survey to provide feedback on the workload allocation model. Survey results indicated that staff and managers found the model useful for evaluating and quantifying workloads. Managers believed the model would be useful for preparing business cases and benchmarking staff workloads. Recommendations for improvements to the workload mapping tool were also identified. What is known about the topic? Workload allocation models have been identified as a valuable means of evaluating and managing AH workloads. Current models do not account for all tasks undertaken by AH clinicians or are applicable to only a specific AH discipline. There is a paucity of workload allocation models suitable for use across AH disciplines. What does this paper add? This paper demonstrates the effectiveness of an AH workload allocation model that incorporates the NAHCC Health Activity Classification that can be used across AH disciplines and work sites. What are the implications for practitioners? This new workload allocation model provides AH managers with a mapping tool that provides a high level of detail of non-patient activities, and guidelines for calculating procedure times that can be used to effectively manage staff workloads, benchmark existing services and plan for new services. Critical evaluation of staff workloads will allow managers to maximise allied health human resources and hence provide better patient outcomes.

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Roy, Abhishek, Alekh Jindal, Priyanka Gomatam, Xiating Ouyang, Ashit Gosalia, Nishkam Ravi, Swinky Mann, and Prakhar Jain. "SparkCruise." Proceedings of the VLDB Endowment 14, no. 12 (July 2021): 3122–34. http://dx.doi.org/10.14778/3476311.3476388.

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Today cloud companies offer fully managed Spark services. This has made it easy to onboard new customers but has also increased the volume of users and their workload sizes. However, both cloud providers and users lack the tools and time to optimize these massive workloads. To solve this problem, we designed SparkCruise that can help understand and optimize workload instances by adding a workload-driven feedback loop to the Spark query optimizer. In this paper, we present our approach to collecting and representing Spark query workloads and use it to improve the overall performance on the workload, all without requiring any access to user data. These methods scale with the number of workloads and apply learned feedback in an online fashion. We explain one specific workload optimization developed for computation reuse. We also share the detailed analysis of production Spark workloads and contrast them with the corresponding analysis of TPC-DS benchmark. To the best of our knowledge, this is the first study to share the analysis of large-scale production Spark SQL workloads.

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Misra, Joya, Alexandra Kuvaeva, Kerryann O’meara, Dawn Kiyoe Culpepper, and Audrey Jaeger. "Gendered and Racialized Perceptions of Faculty Workloads." Gender & Society 35, no. 3 (April 14, 2021): 358–94. http://dx.doi.org/10.1177/08912432211001387.

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Faculty workload inequities have important consequences for faculty diversity and inclusion. On average, women faculty spend more time engaging in service, teaching, and mentoring, while men, on average, spend more time on research, with women of color facing particularly high workload burdens. We explore how faculty members perceive workload in their departments, identifying mechanisms that can help shape their perceptions of greater equity and fairness. White women perceive that their departments have less equitable workloads and are less committed to workload equity than white men. Women of color perceive that their departments are less likely to credit their important work through departmental rewards systems than white men. Workload transparency and clarity, and consistent approaches to assigning classes, advising, and service, can reduce women’s perceptions of inequitable and unfair workloads. Our research suggests that departments can identify and put in place a number of key practices around workload that will improve gendered and racialized perceptions of workload.

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Gabbett, Tim J., Billy Hulin, Peter Blanch, Paul Chapman, and David Bailey. "To Couple or not to Couple? For Acute:Chronic Workload Ratios and Injury Risk, Does it Really Matter?" International Journal of Sports Medicine 40, no. 09 (July 10, 2019): 597–600. http://dx.doi.org/10.1055/a-0955-5589.

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AbstractWe examined the association between coupled and uncoupled acute:chronic workload ratios (ACWR) and injury risk in a cohort of 28 elite cricket fast bowlers (mean±SD age, 26±5 yr). Workloads were estimated using the session rating of perceived exertion (session-RPE). Coupled ACWRs were calculated using a 1-week acute workload and 4-week chronic workload (acute workload was included in the chronic workload calculation), whereas uncoupled ACWRs used the most recent 1-week acute workload and the prior 3-week chronic workload (acute workload was not included in the chronic workload calculation). A nearly perfect relationship (R2=0.99) was found between coupled and uncoupled ACWRs. Using a percentile rank method, no significant differences in injury risk were found between the coupled and uncoupled ACWR. Higher ACWRs were associated with increased injury likelihood for both coupled and uncoupled methods, however there were no significant differences in injury risk between coupled and uncoupled ACWRs. Our data demonstrates that both coupled and uncoupled ACWRs produce the same injury likelihoods. Furthermore, our results are consistent with previous studies: higher ACWRs are associated with greater risk, irrespective of whether acute and chronic workloads are coupled or uncoupled.

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D. Hanabaratti, Kavita, and Rudragoud Patil. "Efficient algorithm for replanning web service composition." Indonesian Journal of Electrical Engineering and Computer Science 31, no. 1 (July 1, 2023): 491. http://dx.doi.org/10.11591/ijeecs.v31.i1.pp491-500.

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Web-service-composition (WSC) workload execution inside a hybrid cloud environment is challenging. A dynamic approach for allocating resources to various tasks, as well as associated sub-tasks having a satisfactory quality-ofservice (QoS) requirement, is necessary for the present real-time demand. As a result of focusing primarily on decreasing processing time as well as cost, current approaches improve latency as well as energy while executing a given workload. This study introduces an efficient re-planning (ERP) algorithm for running many scientific workloads inside a heterogeneous cloud environment, which is designed to address some of the shortcomings of previous approaches. With a changing workload, this study details a technique to improve the WSC's availability as well as robustness. The workload's processing energy requirements are reduced as a result. The montageworkflow has been used to validate the research findings. Comparison with the current heterogeneous earliest finish time (QL-HEFT) algorithm demonstrates that its ERP-WSC approach is much more efficient and reliable.

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Hudaningsih, Nurul. "ANALISIS BEBAN KERJA MENTAL PADA STAF UNIT PELAKSANA TEKNIS DENGAN MENGGUNAKAN METODE NASA TLX (STUDI KASUS: UNIVERSITAS TEKNOLOGI SUMBAWA)." Jurnal TAMBORA 3, no. 3 (October 16, 2019): 91–100. http://dx.doi.org/10.36761/jt.v3i3.401.

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Physical and mental activity is the main point that causes the workload to be commonly experienced by the staff. Therefore, the workload can be said to be a relationship between the ability of workers and the amount of pressure experienced in doing a job. Generally, workloads that are often experienced by technical service Unit staff (UPT) are mental workloads that are caused by working environment conditions (universities), tolerance in work and the amount of pressure experienced in the work. The scope that became the focus in this research is the Sumbawa University of Technology which has 10 UPT (UPT Library, UPT Language Center, UPT new student admissions, UPT International Office, UPT Scholarship, UPT Cooperation, UPT information technology, UPT Public relations and Protokoler, UPT creative spaces and UPT forest management education and research) which each UPT has different workloads. The measurement of mental workloads in this study uses The NASA TLX method (The National Aeronautics and Space Administration Task Load Index) by means of The feeding and weight-bearing of The filling of the questionnaire by the staff in each UPT. The results showed that the UPT that has the lowest mental workload is the UPT Library (54.5), the moderate mental workload is the UPT Language Center (77.4), the highest mental workload i.e. UPT Scholarship (86.4).

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MacPhee, Maura, V. Dahinten, and Farinaz Havaei. "The Impact of Heavy Perceived Nurse Workloads on Patient and Nurse Outcomes." Administrative Sciences 7, no. 1 (March 5, 2017): 7. http://dx.doi.org/10.3390/admsci7010007.

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This study investigated the relationships between seven workload factors and patient and nurse outcomes. (1) Background: Health systems researchers are beginning to address nurses’ workload demands at different unit, job and task levels; and the types of administrative interventions needed for specific workload demands. (2) Methods: This was a cross-sectional correlational study of 472 acute care nurses from British Columbia, Canada. The workload factors included nurse reports of unit-level RN staffing levels and patient acuity and patient dependency; job-level nurse perceptions of heavy workloads, nursing tasks left undone and compromised standards; and task-level interruptions to work flow. Patient outcomes were nurse-reported frequencies of medication errors, patient falls and urinary tract infections; and nurse outcomes were emotional exhaustion and job satisfaction. (3) Results: Job-level perceptions of heavy workloads and task-level interruptions had significant direct effects on patient and nurse outcomes. Tasks left undone mediated the relationships between heavy workloads and nurse and patient outcomes; and between interruptions and nurse and patient outcomes. Compromised professional nursing standards mediated the relationships between heavy workloads and nurse outcomes; and between interruptions and nurse outcomes. (4) Conclusion: Administrators should work collaboratively with nurses to identify work environment strategies that ameliorate workload demands at different levels.

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Більше джерел

Дисертації з теми "Workload"

Weilandt, Jacob. "Individual Workload's Relation to Team Workload : An investigation." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138584.

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There is an ongoing debate regarding the construct of team workload and a central point in that debate is team workload’s relation to individual workload. This study set out to investigate this relationship. To assess the participants workload a microworld called C3Fire was used to simulate a complex control situation in which teams had to cooperate to complete the task of fighting a forest fire. Twelve teams that consisted of four members in each team were recruited. In the microworld each member of the team took on one out of four separate roles and completed three different scenarios with varying degree of difficulty in C3Fire. After each scenario, a number of questionnaires aimed at gauging different aspects of the teams’ experience in the microworld was administered. The questionnaire in focus of the current study was the DATMA questionnaire, which was used to measure individual workload and team workload. To assert the relationship between the two constructs a multiple linear regression was conducted. The results provided showed that individual workload could be used as a significant predictor for modeling team workload. The study therefore concludes that there is evidence for a relationship in which each team members individual workload could be the parts of the total sum of team workload.

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Davies, Ian Peter. "Cognitive workload measurement." Thesis, University of Cambridge, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648450.

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Yeo, Jihwang. "WLAN workload characterization." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2825.

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Thesis (M.S.) -- University of Maryland, College Park, 2005.
Thesis research directed by: Dept. of Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Otoom, Mwaffaq Naif. "Capacity Metric for Chip Heterogeneous Multiprocessors." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/26332.

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The primary contribution of this thesis is the development of a new performance metric, Capacity, which evaluates the performance of Chip Heterogeneous Multiprocessors (CHMs) that process multiple heterogeneous channels. Performance metrics are required in order to evaluate any system, including computer systems. A lack of appropriate metrics can lead to ambiguous or incorrect results, something discovered while developing the secondary contribution of this thesis, that of workload modes for CHMs â or Workload Specific Processors (WSPs). For many decades, computer architects and designers have focused on techniques that reduce latency and increase throughput. The change in modern computer systems built around CHMs that process multi-channel communications in the service of single users calls this focus into question. Modern computer systems are expected to integrate tens to hundreds of processor cores onto single chips, often used in the service of single users, potentially as a way to access the Internet. Here, the design goal is to integrate as much functionality as possible during a given time window. Without the ability to correctly identify optimal designs, not only will the best performing designs not be found, but resources will be wasted and there will be a lack of insight to what leads to better performing designs. To address performance evaluation challenges of the next generation of computer systems, such as multicore computers inside of cell phones, we found that a structurally different metric is needed and proceeded to develop such a metric. In contrast to single-valued metrics, Capacity is a surface with dimensionality related to the number of input streams, or channels, processed by the CHM. We develop some fundamental Capacity curves in two dimensions and show how Capacity shapes reveal interaction of not only programs and data, but the interaction of multiple data streams as they compete for access to resources on a CHM as well. For the analysis of Capacity surface shapes, we propose the development of a demand characterization method in which its output is in the form of a surface. By overlaying demand surfaces over Capacity surfaces, we are able to identify when a system meets its demands and by how much. Using the Capacity metric, computer performance optimization is evaluated against workloads in the service of individual users instead of individual applications, aggregate applications, or parallel applications. Because throughput was originally derived by drawing analogies between processor design and pipelines in the automobile industry, we introduce our Capacity metric for CHMs by drawing an analogy to automobile production, signifying that Capacity is the successor to throughput. By developing our Capacity metric, we illustrate how and why different processor organizations cannot be understood as being better performers without both magnitude and shape analysis in contrast to other metrics, such as throughput, that consider only magnitude. In this work, we make the following major contributions: â ¢ Definition and development of the Capacity metric as a surface with dimensionality related to the number of input streams, or channels, processed by the CHM. â ¢ Techniques for analysis of the Capacity metric. Since the Capacity metric was developed out of necessity, while pursuing the development of WSPs, this work also makes the following minor contributions: â ¢ Definition and development of three foundations in order to establish an experimental foundation â a CHM model, a multimedia cell phone example, and a Workload Specific Processor (WSP). â ¢ Definition of Workload Modes, which was the original objective of this thesis. â ¢ Definition and comparison of two approaches to workload mode identification at run time; The Workload Classification Model (WCM) and another model that is based on Hidden Markov Models (HMMs). â ¢ Development of a foundation for analysis of the Capacity metric, so that the impact of architectural features in a CHM may be better understood. In order to do this, we develop a Demand Characterization Method (DCM) that characterizes the demand of a specific usage pattern in the form of a curve (or a surface in general). By doing this, we will be able to overlay demand curves over Capacity curves of different architectures to compare their performance and thus identify optimal performing designs.
Ph. D.

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Bowers, Drew. "Effects of Subjective Workload Measurement During a Workload Transition on Task Performance." University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1405001490.

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Hajek, Wilfried. "Workload Adaptive Cruise Control." Doctoral thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-203175.

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This doctoral thesis focuses on the modification of ACC to include actual driver workload in the context of automatic headway change. ACC is a driver assistance system that automatically maintains a preliminary defined speed and permits a driver to perform manual headway changes. As drivers show worse (brake) reaction times under high workload situations, the system increases headway accordingly. Driver workload is estimated based on physiological data. Here, we investigate the possibilities of such a system, assuming that physiological sensors can be implemented in future vehicles. The thesis consists of three parts: In the first part, the theoretical background is described and a suitable theoretical model is developed; in the second part, experiments are described, and in the last part, results are discussed. Altogether four experiments support this thesis: 1. The first experiment investigates the foundational relationships between physiology, brake reaction time and workload level. The study employs a simulator setting and results show that physiological data, such as heart rate and skin conductance, permit the identification of different workload levels. These findings validate the results of other studies showing that workload leads to an increase in reaction time. These results could only be validated between the extremes “no-workload” and “high workload” situations. 2. The second experiment simulates an ideal workload-adaptive cruise control (WACC) system. In a simulator setting, system acceptance and awareness are studied, with a view toward future implementation in a real car. The results show better acceptance of WACC in comparison with ACC when subjects receive additional information about the new system. This is because subjects do not perceive changes in distance under high workload conditions. 3. The third experiment focuses on acceptance of the simulated system in on-road conditions. In this study, WACC is integrated in the car and is operated using a MATLAB model. The experiment shows that more subjects notice changes in distance in the on-road condition. In general WACC is preferred over ACC; it is especially these subjects who do not notice changes in distance, who value WACC more than ACC. With the aim of implementing an operational WACC that is capable of adjusting distance according to changes in physiological data, a workload algorithm is developed. 4. The fourth experiment validates the workload algorithm. Results of the algorithm are compared with recordings of the activated workload task and detection rate is calculated. The detection of workload periods was feasible in nearly every case and detection rate was favorable, especially if one considers lags due to design-related latency periods. The experiments presented here indicate that workload is detectable in physiological data and that it influences brake reaction time. Further, we provide evidence pointing to the technical possibility of implementing WACC as well as positive acceptance. The results have been published as an article and are part of this thesis. Also, some parts of the thesis are published as a book chapter (see footnotes). Another publication is in preparation, coauthored by diploma thesis students, who are supervised by the author (consult footnotes). This dissertation is composed, in part, of these publications. References to page numbers of the diploma theses are given to ensure correspondence. The author escorted the topic WACC from the beginning to the end. Sometimes students were involved and intensively supervised, from a thematic as well as a personnel guidance perspective. The author planned the whole project and executed studies and calculations. His psychology insights were not only limited to the discipline of psychology but were furthermore, with the help of students, interdisciplinarily expanded to the subject of informatics. Every study and every result which is presented within this work, was conducted or achieved by the author or (if students supported him) was discussed with the author in weekly discussions (and often several times a day). In these discussions the author provided new ideas and corrections if necessary. Apart from that, the author looked after the fulfillment of the central theme, implemented his psychological knowledge on a daily basis and provided his expertise to complement interdisciplinary point of views. He discussed the central theme as well as details with external partners like the MIT AgeLab as well as professors of the European Union from the adaption project (a project aimed at educating future researchers which includes involvement of highly important commercial and educational partners) and beyond. In this time he also visited conferences and accumulated knowledge which led to the successful achievements of the main objective and he was relevant in reaching the common goals of the adaption project. Furthermore he presented the results of the scientific work on a conference, workshops and in written publications. Within BMW Group Research and Technology, he identified important department- and project- partners and combined the knowledge to a result which benefits science and economy
In dieser Dissertation wird eine Abwandlung des Active Cruise Control (ACC) untersucht, das zusätzlich die Belastung (Workload) des Fahrers als Parameter betrachtet, um den Abstand zum Vordermann automatisiert zu verändern. Bei diesem ACC handelt es sich um ein Fahrerassistenzsystem, das automatisiert die eingestellte Geschwindigkeit hält und eine manuelle (durch den Nutzer ausgelöste) Abstandsveränderung zum Vordermann ermöglicht. Da sich die Bremsreaktionszeit von Fahrern in hohen Belastungssituationen verschlechtert, soll das entwickelte Workload-adaptive Cruise Control (WACC) in Situationen hoher Belastung den Abstand zum Vordermann automatisiert erhöhen. Die Belastung des Fahrers soll durch physiologische Daten ermittelt werden. Die vorliegende Arbeit untersucht die Möglichkeit eines solchen Systems unter der Annahme, dass in Zukunft geeignete physiologische Sensoren ins Auto eingebaut werden können. Die Arbeit besteht aus drei Teilen: • Im ersten Teil wird der theoretische Hintergrund beschrieben und ein passendes theoretisches Modell entwickelt. • Im zweiten Teil werden die durchgeführten Experimente beschrieben. • Im dritten Teil werden die Ergebnisse diskutiert. Insgesamt wurden im Rahmen dieser Arbeit vier Experimente durchgeführt: Das erste Experiment beschäftigte sich mit den grundlegenden Zusammenhängen zwischen Physiologie, Bremsreaktionszeit und Belastungslevel. Wie die Ergebnisse der im Simulator durchgeführten Studie zeigen, können mit physiologischen Daten wie Herzrate, Herzratenvariabilität und Hautleitfähigkeit unterschiedliche Workloadlevel identifiziert werden. Darüber hinaus wurden die Ergebnisse anderer Studien bestätigt, die belegen, dass Workload die Bremsreaktionszeit erhöht, wobei dies nur im Kontrast zwischen den Extrembereichen „kein Workload“ und „hoher Workload“ nachweisbar ist. Das zweite Experiment diente der Simulierung eines perfekten WACC. Im Simulator wurden Akzeptanz und Systemwahrnehmung getestet, um vor der Implementierung in ein Realfahrzeug weitere Erkenntnisse zu gewinnen. Im Vergleich zum ACC wurde das WACC von den Probanden besser akzeptiert, nachdem sie zusätzliche Informationen zum neuen System erhalten hatten. Der wesentliche Grund dafür ist, dass die Probanden ohne Informationen die Abstandsveränderung bei hohem Workload nicht realisieren. Das dritte Experiment fokussierte auf die Akzeptanz des simulierten Systems unter Realbedingungen. Das WACC wurde in das Auto integriert und durch ein MATLAB Modell gesteuert. Als Ergebnis zeigte sich, dass unter Realbedingungen mehr Probanden die Abstandsveränderung realisieren als im Simulator. Generell wird das WACC präferiert – vor allem jene Probanden, die die Abstandsveränderung nicht realisieren, bewerten das WACC besser als das ACC. Mit den in diesem Teilexperiment erhobenen Daten wurde ein Algorithmus zur Workloaderkennung entwickelt. Auf dieser Basis konnte im letzten Experiment ein Realsystem implementiert werden, das aufgrund physiologischer Daten den Abstand verändert. Das vierte Experiment beschäftigte sich mit der Validierung des Algorithmus zur Workloaderkennung. Die Ergebnisse des Algorithmus wurden mit der aufgezeichneten Aktivierung des Workloadtasks verglichen und eine Detektionsrate ermittelt. Die Detektion der Workloadperioden gelingt in fast allen Fällen und die Detektionsrate ist vielversprechend, gerade wenn man Verzögerungen berücksichtigt, die wegen der Latenzzeit körperlicher Reaktionen nicht verbesserungsfähig sind. In den vorliegenden Experimenten konnte gezeigt werden, dass Workload über die Physiologie messbar ist und sich auf die Bremsreaktionszeit auswirkt. Darüber hinaus wurde gezeigt, dass ein WACC technisch machbar ist und die Ergebnisse lassen außerdem auf eine hohe Akzeptanz schließen. Die Forschungsergebnisse wurden in einem Artikel publiziert, der auch in dieser Dissertation zu finden ist. Teile der vorliegenden Arbeit wurden außerdem als Buchkapitel veröffentlicht (siehe Fußnoten), eine weitere Publikation mit den vom Autor umfassend betreuten Diplomanden ist in Ausarbeitung. Um die Nachvollziehbarkeit zu gewährleisten, wurde auf die Seitenzahlen der entsprechenden Diplomarbeiten verwiesen. Als Autor dieser Dissertation habe ich das Thema WACC von Anfang bis Ende selbst erarbeitet bzw. wurden Studenten eingesetzt und angeleitet, wo es sinnvoll erschien. Neben der fachlichen wie personellen Führung der Studenten umfassten meine Aufgaben die Planung des Gesamtprojekts, das Durchführen der Studien und die Berechnung von Kennzahlen – sowohl in meinem eigenen psychologischen Fachgebiet als auch interdisziplinär mit Hilfe von Experten aus der Informatik. Jedes Ergebnis, das in dieser Arbeit präsentiert wird, wurde entweder von mir selbst erzielt oder – sofern ich dabei von Studenten unterstützt wurde – mit mir in wöchentlichen (oft auch mehrmals täglich stattfindenden Meetings) besprochen. Wichtig war mir als Autor, einen durchgängigen Weg zur Entwicklung eines WACC zu wahren, mein psychologisches Fachwissen täglich anzuwenden und in interdisziplinären Aufgaben und Diskussionen meine Perspektive einzubringen. Besonders wichtig war dabei die Diskussion des Gesamtprojekts und der Details mit externen Partnern wie dem MIT AgeLab oder Professoren aus der Europäischen Union im Rahmen des Adaptation Projekts (ein von der EU gefördertes Projekt zur Ausbildung von Forschern, unter Einbindung wirtschaftlich und wissenschaftlich hochrangiger Partner). Durch die Präsentation der Ergebnisse auf Konferenzen, in Workshops und Publikationen konnte ich einen Beitrag dazu leisten, um die Adaptation-Ziele zu erreichen. Innerhalb der BMW Group Forschung und Technik habe ich darauf geachtet, relevante Schnittstellen- und Projektpartner zu identifizieren und das erlangte Wissen zu einem Ergebnis zu verbinden, das Wissenschaft und Wirtschaft gleichermaßen nützt

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FUNKE, GREGORY J. "THE EFFECTS OF AUTOMATION AND WORKLOAD ON DRIVER PERFORMANCE, SUBJECTIVE WORKLOAD, AND MOOD." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1193000603.

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Sellers, James Michael. "Team Workload Questionnaire (TWLQ): Development and Assessment of a Subjective Measure of Team Workload." Thesis, University of Canterbury. Psychology, 2013. http://hdl.handle.net/10092/8971.

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The present research developed and assessed the Team Workload Questionnaire (TWLQ). Despite extensive workload studies, little research has been conducted on the workload experienced by teams. Team workload has largely been ignored by research with no validated theory constructed or dedicated team workload measures available to researchers and practitioners. The research was conducted in two studies with study 1 focusing on the development of the TWLQ with 216 members of sports team completing a team workload measure after games or practise. In study 2, 14 dyadic teams performed two sessions of an unmanned aerial vehicle (UAV) search-and-rescue task. The TWLQ was used to measure the team workload demand of the task. Study 1: Principle Axis Factoring method with Direct Oblimin rotation indicated three separate factors for the TWLQ with the factors classified as Task Workload, Team Workload, and Task-Team Balancing. Study 2: The TWLQ exhibited differential sensitivity, with the three factors measuring unique components of the workload demands in teams. The TWLQ is a valid and reliable subjective measure that can be used to assess the workload demand in team tasks. It provides researchers a tool to advance the understating of team workload and gives practitioners the means to assess the workload demands of team tasks in applied settings.

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Ghasempour, Mohsen. "Workload-adaptation in memory controllers." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/workloadadaptation-in-memory-controllers(9087e7a1-755b-4e2b-a97e-1bfcde7968b4).html.

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Advanced development in processor design, increasing the heterogeneity of computer system, by involving Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs) and custom accelerators, and increasing the number of cores and threads in such systems puts extra pressure on the main memory, demanding a higher performance. Current computing trends are putting ever more pressure on main memory. In modern computer systems, this is generally Dynamic Random Access Memory (DRAM) which consists of a multi-level access hierarchy (e.g. Rank, Bank, Row etc.). This heterogeneity of structure implies different access latencies (and power consumption), resulting in performance differences according to memory access patterns. DRAM controllers manage access and satisfy the timing constraints and now employ complex scheduling and prediction algorithms to mitigate the effect on performance. This complexity can limit the scalability of a controller with the size of memory, while maintaining performance. The focus of this PhD thesis is to improve performance, reliability and scalability (with respect to memory size) of DRAM controllers. To this end, it covers three significant contributors to the performance and reliability of a memory controller: ‘Address Mapping’, ‘Page Closure Policies’ and ‘Reliability Monitoring’. A detailed DRAM simulator is used as an evaluation platform throughout this work. The following contributions are presented in this thesis. Hybrid Address-based Page PolicY (HAPPY): Memory controllers have used static page-closure policies to decide whether a row should be left open (open-page policy) or closed immediately (close-page policy) after use. The appropriate choice can reduce the average memory latency. Since access patterns are dynamic, static page policies cannot guarantee to deliver optimum execution time. Hybrid page policies can cover dynamic scenarios and are now implemented in state-of-the-art processors. These switch between open-page and close-page policies by monitoring the access pattern of row hits/conflicts and predicting future behaviour. Unfortunately, as the size of DRAM memory increases, fine-grain tracking and analysis of accesses does not remain practical. HAPPY proposes a compact, memory address-based encoding technique which can maintain or improve page closure predictor performance while reducing the hardware overhead. As a case study, HAPPY is integrated, with a state-of-the-art monitor – the Intel-adaptive open-page policy predictor employed by the Intel Xeon X5650 – and a traditional Hybrid page policy. The experimental results show that using the HAPPY encoding applied to the Intel-adaptive page closure policy can reduce the hardware overhead by 5× for the evaluated 64 GB memory (up to 40× for a 512 GB memory) while maintaining the prediction accuracy. Dynamic Re-arrangement of Address Mapping (DReAM): The initial location of data in DRAMs is determined and controlled by the ‘address-mapping’ and even modern memory controllers use a fixed and runtime-agnostic address-mapping. On the other hand, the memory access pattern seen at the memory interface level will be dynamically changed at run-time. This dynamic nature of memory access pattern and the fixed behaviour of address mapping process in DRAM controllers, implied by using a fixed address-mapping scheme, means that DRAM performance cannot be exploited efficiently. DReAM is a novel hardware technique that can detect a workload-specific address mapping at run-time based on the application access pattern. The experimental results show that DReAM outperforms the best evaluated baseline address mapping by 5%, on average, and up to 28% across all the workloads. A Run-time Memory hot-row detectOR (ARMOR): DRAM needs refreshing to avoid data loss. Data can also be corrupted within a refresh interval by crosstalk caused by repeated accesses to neighbouring rows; this is the row hammer effect and is perceived as a potentially serious reliability and security threat. ARMOR is a novel technique which improves memory reliability by detecting which rows are potentially being “hammered” within the memory controller, which can then insert extra refresh operations. It can detect (and thus prevent) row hammer errors with minimal execution time overhead and hardware requirements. Alternatively by adding buffers inside the memory controller to cache such hammered rows, execution times are reduced with small hardware costs. The ARMOR technique is now the basis of a patent applicant and under process for commercial exploitation. As a final step of this PhD thesis, an adaptive memory controller was developed integrating HAPPY, DReAM and ARMOR into a standard memory controller. The performance and the implementation cost of such an adaptive memory controller were compared against a state-of-the-art memory controller, as a baseline. The experimental results show that the adaptive memory controller outperforms the baseline, on average by 18%, and up to 35% for some workloads, while requiring around 6 KB-900 KB more storage than the baseline to support a wide range of memory sizes (from 4 GB up to 512 GB).

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Cheng, Yue. "Workload-aware Efficient Storage Systems." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/78677.

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The growing disparity in data storage and retrieval needs of modern applications is driving the proliferation of a wide variety of storage systems (e.g., key-value stores, cloud storage services, distributed filesystems, and flash cache, etc.). While extant storage systems are designed and tuned for a specific set of applications targeting a range of workload characteristics, they lack the flexibility in adapting to the ever-changing workload behaviors. Moreover, the complexities in implementing modern storage systems and adapting ever-changing storage requirements present unique opportunities and engineering challenges. In this dissertation, we design and develop a series of novel data management and storage systems solutions by applying a simple yet effective rule---workload awareness. We find that simple workload-aware data management strategies are effective in improving the efficiency of modern storage systems, sometimes by an order of magnitude. The first two works tackle the data management and storage space allocation issues at distributed and cloud storage level, while the third work focuses on low-level data management problems in the local storage system, which many high-level storage/data-intensive applications rely on. In the first part of this dissertation (Chapter~ref{ch:mbal}), we propose and develop MBal, a high-performance in-memory object caching framework with adaptive multi-phase load balancing, which supports not only horizontal (scale-out) but vertical (scale-up) scalability as well. MBal is able to make efficient use of available resources in the cloud through its fine-grained, partitioned, lockless design. In the second part of this dissertation (Chapter~ref{ch:cast} and Chapter~ref{ch:pricing}), we design and build CAST (Chapter~ref{ch:cast}), a Cloud Analytics Storage Tiering solution that cloud tenants can use to reduce monetary cost and improve performance of analytics workloads. The approach takes the first step towards providing storage tiering support for data analytics in the cloud. Furthermore, we propose a hybrid cloud object storage system (Chapter~ref{ch:pricing}) that could effectively engage both the cloud service providers and cloud tenants via a novel dynamic pricing mechanism. In the third part of this dissertation (Chapter~ref{ch:offline}), targeting local storage, we explore offline algorithms for flash caching in terms of both hit ratio and flash lifespan. We design and implement a multi-stage heuristic by synthesizing several techniques that manage data at the granularity of a flash erasure unit (which we call a container) to approximate the offline optimal algorithm. In the fourth part of this dissertation (Chapter~ref{ch:turnkey}), we are focused on how to enable fast prototyping of efficient distributed key-value stores targeting a proxy-based layered architecture. In this work, we design and build {con}, a framework that significantly reduce the engineering effort required to build a full-fledged distributed key-value store. Our dissertation shows that simple workload-aware data management strategies can bring huge benefit in terms of both efficiency (i.e., performance, monetary cost, etc.) and flexibility (i.e., ease-of-use, ease-of-deployment, programmability, etc.). The principles of leveraging workload dynamicity and storage heterogeneity can be used to guide next-generation storage system software design, especially when being faced with new storage hardware technologies.
Ph. D.

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Книги з теми "Workload"

Großmann, Daniel, Christin Engel, Justus Junkermann, and Tobias Wolbring, eds. Studentischer Workload. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28931-7.

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Washington (State). Dept. of Corrections., ed. Workload study 1998. [Olympia, Wash.]: The Department, 1999.

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Margaret, Beardsley, Parker Vivienne, and Secondary Heads Association, eds. Managing the workload. Leicester: SHA, 1996.

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1953-, Hancock Peter A., and Meshkati Najmedin, eds. Human mental workload. Amsterdam: North-Holland, 1988.

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J, Lysaght Robert, and U.S. Army Research Institute for the Behavioral and Social Sciences, eds. Operator workload: Comprehensive review and evaluation of operator workload methodologies. Alexandria, Va: United States Army Research Institute for the Behavioral and Social Sciences, 1989.

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Dilley, John A. Web server workload characterization. Palo Alto, CA: Hewlett-Packard Laboratories, Technical Publications Department, 1996.

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Letmanyi, Helen. Guide on workload forecasting. Gaithersburg, MD: U.S. Dept. of Commerce, National Bureau of Standards, 1985.

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Sabharwal, Navin, and Subramani Kasiviswanathan. Workload Automation Using HWA. Berkeley, CA: Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-8885-6.

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Board, Local Government Management, ed. Occupational therapy workload survey. London: Local Government Management Board, 1997.

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1953-, Hancock Peter A., and Desmond Paula A, eds. Stress, workload, and fatigue. Mahwah, N.J: Lawrence Erlbaum Associates, 2001.

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Частини книг з теми "Workload"

Campbell, Tavis S., Jillian A. Johnson, Kristin A. Zernicke, Christopher Shaw, Kazuo Hara, Kazuo Hara, Susan Folkman, et al. "Workload." In Encyclopedia of Behavioral Medicine, 2068–69. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_934.

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Wickens, Chris, and Pamela S. Tsang. "Workload." In APA handbook of human systems integration., 277–92. Washington: American Psychological Association, 2015. http://dx.doi.org/10.1037/14528-018.

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Jacobs, Karen, Miranda Hellman, Jacqueline Markowitz, and Ellen Wuest. "Workload." In Encyclopedia of Behavioral Medicine, 2356. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_934.

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Großmann, Daniel, Christin Engel, Justus Junkermann, and Tobias Wolbring. "Konzeption und Messung studentischen Workloads. Ein Überblick zu Entstehung, Stand und Herausforderungen." In Studentischer Workload, 3–30. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28931-7_1.

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Schulmeister, Rolf. "Chancen und Grenzen einer Anwesenheitspflicht in Lehrveranstaltungen. Ein Studienreview zu Anwesenheit und Lernerfolg." In Studentischer Workload, 253–70. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28931-7_10.

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Nennstiel, Richard, and Rolf Becker. "Hängen die ECTS-Punkte von Lehrveranstaltungen mit dem studentischen Workload zusammen?" In Studentischer Workload, 273–92. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28931-7_11.

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Kuhlee, Dina. "Brauchen wir eine Workload-Diskussion? Zur Rolle formaler Studienworkloads für das Lern- und Studierhandeln. Eine empirische Studie bei Lehramtsstudierenden des Master of Education." In Studentischer Workload, 293–312. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28931-7_12.

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Wittenberg, Reinhard. "Studentischer Workload im Bachelorstudium am Fachbereich Wirtschafts- und Sozialwissenschaften der Friedrich-Alexander-Universität Erlangen-Nürnberg von 2007 bis 2018." In Studentischer Workload, 315–34. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28931-7_13.

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Müller, Stefen. "Workload-Erhebungen – Notwendiges Übel oder ungenutzte Chance?" In Studentischer Workload, 335–60. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28931-7_14.

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Großmann, Daniel, and Christin Engel. "Determinanten des studentischen Workloads. Eine Übersicht und Modellskizze." In Studentischer Workload, 31–62. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28931-7_2.

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Тези доповідей конференцій з теми "Workload"

Khanna, Rahul, Mrittika Ganguli, Ananth Narayan, Abhiram R., and Piyush Gupta. "Autonomic Characterization of Workloads Using Workload Fingerprinting." In 2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM). IEEE, 2014. http://dx.doi.org/10.1109/ccem.2014.7015482.

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Matsuura, Anne. "Developing Quantum Workloads for Workload-Driven Co-design." In ISPD '23: International Symposium on Physical Design. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3569052.3578906.

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Kim, Keunsoo, Changmin Lee, Jung Ho Jung, and Won Woo Ro. "Workload synthesis: Generating benchmark workloads from statistical execution profile." In 2014 IEEE International Symposium on Workload Characterization (IISWC). IEEE, 2014. http://dx.doi.org/10.1109/iiswc.2014.6983051.

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Drobinsky, Sergey, Patrick Korte, Rastislav Pjontek, Armin Janß, Verena Nitsch, and Klaus Radermacher. "Development of a Prospective Method for Rating Surgical Task Workloads." In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004382.

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Surgical adverse events can have serious consequences for patients ranging from temporary injuries to death. Thereby, up to 40% of surgical adverse events are preventable and over 60% of causal factors were found to be linked to human factors. To improve surgical performance and safety, computer-assisted surgical (CAS) systems can be used to reduce excessive workloads. This paper presents a method for prospective assessment of surgical task workloads. S-TAWL, developed with the support of a senior neurosurgeon and a usability engineer, consists of three parts: surgical task decomposition, workload rating scale application, and performance shaping factors characterization. For the proposed rating scales, composed of reference operators, relative workloads were determined by 11 neurosurgeons through pairwise comparison. Afterwards, one senior neurosurgeon, not involved in method development, analysed workloads of four common surgical tasks with the proposed method S-TAWL and a reference workload rating method Surg-TLX. Qualitatively, S-TAWL provides more detailed information about workloads with respect to human resources compared to the reference method. Quantitatively, however, the reliability of the results is still limited, as indicated by high standard deviations. Further research is needed to develop reliable and valid rating scales, compute compound workloads and identify overloads. Incorporating quantitative workload assessment in prospective human performance analysis will provide valuable information for targeted model-based design of assistance systems, supporting safe and successful surgery in the future.

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Shishira, S. R., A. Kandasamy, and K. Chandrasekaran. "Workload Characterization." In the 7th International Conference. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3154979.3155003.

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Truschzinski, Martina. "Modeling Workload." In HRI '17: ACM/IEEE International Conference on Human-Robot Interaction. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3029798.3038408.

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Genkin, Mikhail, and Frank Dehne. "Autonomic Workload Change Classification and Prediction for Big Data Workloads." In 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006149.

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Bash, Cullen, and George Forman. "Data Center Workload Placement for Energy Efficiency." In ASME 2007 InterPACK Conference collocated with the ASME/JSME 2007 Thermal Engineering Heat Transfer Summer Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/ipack2007-33129.

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Data center costs for computer power and cooling have been steadily increasing over the past decade. Much work has been done in recent years on understanding how to improve the delivery of cooling resources to IT equipment in data centers, but little attention has been paid to the optimization of heat production by considering the placement of application workload. Because certain physical locations inside the data center are more efficient to cool than others, this suggests that allocating heavy computational workloads onto those servers that are in more efficient places might bring substantial savings. This paper explores this issue by introducing a workload placement metric that considers the cooling efficiency of the environment. Additionally, results from a set of experiments that utilize this metric in a thermally isolated portion of a real data center are described. The results show that the potential savings is substantial and that further work in this area is needed to exploit the savings opportunity.

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Holze, Marc, Ali Haschimi, and Norbert Ritter. "Towards workload-aware self-management: Predicting significant workload shifts." In 2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010). IEEE, 2010. http://dx.doi.org/10.1109/icdew.2010.5452738.

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Golfarelli, Matteo, and Ettore Saltarelli. "The workload you have, the workload you would like." In the 6th ACM international workshop. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/956060.956075.

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

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

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Schwarz, Kurt F., IV Brooks, and Thomas L. Forecasting Contracting Workload. Fort Belvoir, VA: Defense Technical Information Center, April 1989. http://dx.doi.org/10.21236/ada211935.

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Austin, Brian, Tina Butler, Richard Gerber, Cary Whitney, Nicholas Wright, Woo-Sun Yang, and Zhengji Zhao. Hopper Workload Analysis. Office of Scientific and Technical Information (OSTI), May 2014. http://dx.doi.org/10.2172/1163230.

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

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Hook, Audrey A., and R. D. Lehman. Ada Validation Workload. Fort Belvoir, VA: Defense Technical Information Center, January 1988. http://dx.doi.org/10.21236/ada224027.

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Lysaght, Robert J., Susan G. Hill, A. O. Dick, Brian D. Plamondon, and Paul M. Linton. Operator Workload: Comprehensive Review and Evaluation of Operator Workload Methodologies. Fort Belvoir, VA: Defense Technical Information Center, June 1989. http://dx.doi.org/10.21236/ada212879.

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Letmanyi, Helen. Guide on workload forecasting. Gaithersburg, MD: National Bureau of Standards, 1985. http://dx.doi.org/10.6028/nbs.sp.500-123.

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Rench, Michael E. Auditory Workload Assessment, Volume 1. Fort Belvoir, VA: Defense Technical Information Center, October 2000. http://dx.doi.org/10.21236/ada391826.

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Staunton, Dr Michael Staunton, Dr Kevin Bailey, Dr Anne Bergin, Dr David Honan, Dr John Kennedy, Dr Avine Lydon, Dr Geraldine Maloney, et al. Workload for consultant anaesthetists in Ireland. The Association of Anaesthetists of Great Britain and Ireland, April 2010. http://dx.doi.org/10.21466/g.wfcaiia.2010.

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