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Workloads of the Future
2008
IEEE Design & Test of Computers
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Whereas today a billion mobile phones are sold per year, in the near future perhaps upwards of a trillion sensory nodes per year will be sold and deployed, with the majority of these connected wirelessly ...
will be of the essence. ...
The authors of this article characterize these workloads of the future and argue for a new set of benchmarks to guide the exploration and optimization of future systems. - There have been some efforts ...
doi:10.1109/mdt.2008.118
fatcat:4uyaaojnsbajpj3dyzpcbdyx5y
GlobeTraff: A Traffic Workload Generator for the Performance Evaluation of Future Internet Architectures
2012
2012 5th International Conference on New Technologies, Mobility and Security (NTMS)
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Having identified important limitations of the current Internet architecture, several research initiatives have engaged in the design of new architectures for the Internet of the Future. ...
To this end, we have designed and implemented GlobeTraff, a traffic workload generator for the creation of synthetic traffic mixes. ...
However, the advent of clean slate approaches for the future Internet changes this application-specific point of view. ...
doi:10.1109/ntms.2012.6208742
dblp:conf/ntms/KatsarosXP12
fatcat:3yymxzbyz5fmvmafdpvmgd2c6i
On the memory system requirements of future scientific applications: Four case-studies
2011
2011 IEEE International Symposium on Workload Characterization (IISWC)
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Based on the analysis of their instrumented execution, we project some performance requirements from future memory systems serving large-scale chip multiprocessors (CMPs). ...
In addition, we estimate the impact of memory system performance on the amount of instruction stalls, as well as on the real computational performance, using the number of floating point operations per ...
Acknowledgements This research is supported by the Consolider contract number TIN2007-60625 from the Ministry of Science and Innovation of Spain and the TERAFLUX project (ICT-FP7-249013). Y. ...
doi:10.1109/iiswc.2011.6114176
dblp:conf/iiswc/PavlovicER11
fatcat:npkantdiavebvhltafgnucpttq
Workload of diagnostic radiologists in the foreseeable future based on recent scientific advances: growth expectations and role of artificial intelligence
2021
Insights into Imaging
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The direct contribution of each study to patient care and its effect on the workload of diagnostic radiologists (i.e., number of examinations performed per time unit) was assessed. ...
Objective To determine the anticipated contribution of recently published medical imaging literature, including artificial intelligence (AI), on the workload of diagnostic radiologists. ...
Since the effect of AI on future workload remains unclear, and associated practical consequences are very relevant, it is crucial to fill in this knowledge gap. ...
doi:10.1186/s13244-021-01031-4
pmid:34185175
fatcat:bwqlibhhojgzvatj34pnaaridq
EFFECTS OF COGNITIVE WORKLOAD ON DECISION ACCURACY, SHOOTING PERFORMANCE, AND CORTICAL ACTIVITY OF SOLDIERS
2006
Transformational Science and Technology for the Current and Future Force
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Results from analyses of the subjective report data revealed that time stress and decision load main effects significantly influenced workload perceptions. ...
Overall, the results suggest that time stress had the most profound and widespread effects on workload perceptions and performance. ...
The subjects completed subjective reports of workload (Subjective Workload Assessment Technique, SWAT) and stress (Subjective Ratings of Events, SRE) immediately following the completion of each scenario ...
doi:10.1142/9789812772572_0046
fatcat:ljnnrpqaqbg7tdgzqa62l6ym2u
Exploring Machine Learning Approaches for Classifying Mental Workload using fNIRS Data from HCI Tasks
2019
Proceedings of the Halfway to the Future Symposium 2019 on - HTTF 2019
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We also make recommendations for avenues of future work that are most promising for the machine learning of fNIRS data. ...
To provide additional practical advice for future brain-computer interaction systems, we conclude by discussing the limitations and data-preparation needs of different machine learning approaches. ...
Michel Valstar for their advice on the application of machine learning and more specifically deep learning for fNIRS data. ...
doi:10.1145/3363384.3363392
dblp:conf/httf/BenerradiMMC019
fatcat:czrexo7gkzgffbzdcb6asiujdu
Medical workforce review using the RCP guidance on safe medical staffing demonstrating wide variation of workload to workforce ratio between medical teams within a single trust
2019
Future healthcare journal
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With this data, we then: > determined the ratio of workload to workforce per team, and compared between teams > compared the number of doctors needed as per the RCP guidance with actual staffi ng levels ...
Workload was calculated as 'average hours of work required per week per team' based on estimations in the RCP report. ...
doi:10.7861/futurehosp.6-2s-s44
pmid:31572939
pmcid:PMC6752413
fatcat:rrs6xzijnzfbbciytww5mqvo2a
Medical workforce review using the RCP guidance on safe medical staffing demonstrating wide variation of workload to workforce ratio between medical teams within a single trust
2019
Future healthcare journal
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With this data, we then: > determined the ratio of workload to workforce per team, and compared between teams > compared the number of doctors needed as per the RCP guidance with actual staffi ng levels ...
Workload was calculated as 'average hours of work required per week per team' based on estimations in the RCP report. ...
doi:10.7861/futurehealth.6-2-s44
fatcat:qqz3lxci4ncnzbh4x23s3r664m
Work-Home Interference, Perceived Total Workload, and the Risk of Future Sickness Absence Due to Stress-Related Mental Diagnoses Among Women and Men: a Prospective Twin Study
2017
International Journal of Behavioral Medicine
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The aim was to study whether work-home interference and perceived total workload predict SA due to stress-related mental diagnoses, or SA due to other mental diagnoses, among women and men, when adjusting ...
Results Each one unit increase in work-to-home and home-towork conflicts, and perceived total workload was associated with higher odds for SA due to stress-related mental diagnoses ...
All authors contributed in designing the study and to the interpretation of the results and to the writing and approval of the final article. ...
doi:10.1007/s12529-017-9669-9
pmid:28639237
pmcid:PMC5803287
fatcat:2lipapof5ba33alz6dz7uztfbq
An Eye for the Air Traffic Controller Workload
2010
Journal of the Transportation Research Forum
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The purpose of this paper is to outline an approach for workload measurements and optimization of air traffic systems and displays that match controller needs. ...
Such systems, once developed, will increase operator and system efficiency and increase the safety of airline operations. ...
Because the nature of operator tasks and workload are likely to change, workload assessments play an important role in the development of future control systems. ...
doi:10.5399/osu/jtrf.46.3.676
fatcat:7kb7bx46onbbjj4vggjc3kcpte
Workload Analysis and Demand Prediction of Enterprise Data Center Applications
2007
2007 IEEE 10th International Symposium on Workload Characterization
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We use a trace based approach for capacity management that relies on i) the characterization of workload demand patterns, ii) the generation of synthetic workloads that predict future demands based on ...
Understanding the nature of enterprise workloads is crucial to properly designing and provisioning current and future services in such pools. ...
The synthetic trace had similar properties as the actual future behavior of the workload. ...
doi:10.1109/iiswc.2007.4362193
dblp:conf/iiswc/GmachRCK07
fatcat:p4ze2xnc35hqbpvhew7bxfgyn4
A Virtual Machine Migration Strategy Based on Time Series Workload Prediction Using Cloud Model
2014
Mathematical Problems in Engineering
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Aimed at resolving the issues of the imbalance of resources and workloads at data centers and the overhead together with the high cost of virtual machine (VM) migrations, this paper proposes a new VM migration ...
By setting the upper and lower workload bounds for host machines, forecasting the tendency of their subsequent workloads by creating a workload time series using the cloud model, and stipulating a general ...
Acknowledgments This work is supported in part by the following Grants ...
doi:10.1155/2014/973069
fatcat:aol5iaaalrazboyu6vf545omwa
Minimum makespan workload dissemination in DTNs
2013
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing - MobiHoc '13
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D2 makes dissemination decisions based on the estimations of the potential computational capacities and the future workloads of DTN nodes. ...
We first investigate the scenario in which each node has access to an oracle that knows global and future knowledge of node mobility, and we propose a centralized polynomial-time optimal algorithm. ...
; and the future workload estimator predicts the expected workload in a node at a future time slot. ...
doi:10.1145/2491288.2491327
dblp:conf/mobihoc/ZhangWL13
fatcat:5hxriitmcnh2ndjeitg4isnq6m
Page 17 of Computer Performance Vol. 5, Issue 4
[page]
1984
Computer Performance
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Sizing future workloads
Gauging the effect of any new application or changes to an existing workload is probably the most difficult task of capacity planning. ...
Even if the above technique does not significantly increase your knowledge of future workloads, at least it makes the planners aware of the extent of your knowledge. ...
Thermal status and workload prediction using support vector regression
2012
2012 International Conference on Energy Aware Computing
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, we propose in this paper using support vector regression (SVR) to predict future processor thermal status as well as the currently running workload. ...
The second model predicts the current workload with a percentage error of 0.08% for a heterogeneous training set of 6 different integer and floating point benchmark workloads. ...
and partly by the University Research Board at the American University of Beirut. ...
doi:10.1109/iceac.2012.6471027
dblp:conf/iceac/StockmanAAK12
fatcat:afr7ara4rjb6bn4hxwkyxt4i74
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