Results 31 to 40 of about 1,735,174 (276)

Automotive automation: Investigating the impact on drivers' mental workload [PDF]

, 1997
Recent advances in technology have meant that an increasing number of vehicle driving tasks are becoming automated. Such automation poses new problems for the ergonomist.
Stanton, N A, Young, M S
core   +6 more sources

Unraveling the Physiological Correlates of Mental Workload Variations in Tracking and Collision Prediction Tasks

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022
Modern work environments have extensive interactions with technology and greater cognitive complexity of the tasks, which results in human operators experiencing increased mental workload.
Alka Rachel John, Avinash K. Singh, Tien-Thong Nguyen Do, Ami Eidels, Eugene Nalivaiko, Alireza Mazloumi Gavgani, Scott Brown, Murray Bennett, Sara Lal, Ann M. Simpson, Sylvia M. Gustin, Kay Double, Frederick Rohan Walker, Sabina Kleitman, John Morley, Chin-Teng Lin   +15 more
doaj   +1 more source

Energy Prediction for Cloud Workload Patterns [PDF]

, 2017
The excessive use of energy consumption in Cloud infrastructures has become one of the major cost factors for Cloud providers to maintain. In order to enhance the energy efficiency of Cloud resources, proactive and reactive management tools are used. However, these tools need to be supported with energy-awareness not only at the physical machine (PM ...
Ibrahim Alzamil, Karim Djemame
openaire   +3 more sources

Cloud Workload Prediction by Means of Simulations [PDF]

Proceedings of the Computing Frontiers Conference, 2017
Clouds hide the complexity of maintaining a physical infrastructure with a disadvantage: they also hide their internal workings. Should users need to know about these details e.g., to increase the reliability or performance of their applications, they would need to detect slight behavioural changes in the underlying system.
Gabor Kecskemeti, Attila Kertész, Zsolt Németh   +2 more
openaire   +4 more sources

MEC Server Status Optimization Framework for Energy Efficient MEC Systems by Taking a Deep-Learning Approach

Future Internet
Reducing energy consumption in a MEC (Multi-Access Edge Computing) system is a critical goal, both for lowering operational expenses and promoting environmental sustainability.
Minseok Koo, Jaesung Park
doaj   +1 more source

ML-Empowered Microservice Workload Prediction by Dual-Regularized Matrix Factorization

Applied Sciences
A technical challenge for workload prediction in microservice systems is how to capture both the dynamic features of workload and evolving dependencies among microservices.
Xiaoxuan Luo, Hong Shen, Wei Ke
doaj   +1 more source

A Novel Mutual Information Based Feature Set for Drivers’ Mental Workload Evaluation Using Machine Learning

Brain Sciences, 2020
Analysis of physiological signals, electroencephalography more specifically, is considered a very promising technique to obtain objective measures for mental workload evaluation, however, it requires a complex apparatus to record, and thus, with poor ...
Mir Riyanul Islam, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum, Pietro Aricò, Gianluca Borghini, Gianluca Di Flumeri   +6 more
doaj   +1 more source

Bayesian Uncertainty Modelling for Cloud Workload Prediction

2022 IEEE 15th International Conference on Cloud Computing (CLOUD), 2022
Providers of cloud computing systems need to manage resources carefully to meet the desired Quality of Service and reduce waste due to overallocation. An accurate prediction of future demand is crucial to allocate resources to service requests without excessive delays.
Andrea Rossi 0010, Andrea Visentin, Steven D. Prestwich, Kenneth N. Brown   +3 more
openaire   +2 more sources

A clinical site workload prediction model with machine learning lifecycle

Healthcare Analytics, 2023
In clinical trial monitoring, substantial resources are allocated to perform source data verification (SDV). SDV ensures accurate and reliable transcription of trial participant information.
Bilal Mirza, Xinyang Li, Kris Lauwers, Bhargava Reddy, Anja Muller, Craig Wozniak, Sina Djali   +6 more
doaj   +1 more source

Workload Characterization for Branch Predictability

CoRR
This manuscript is an archival version of work conducted as part of the author's 2020 Master's at Texas A\&M University under the supervision of Professors Paul Gratz and Daniel A.~Jim\'enez.
FNU Vikas, Paul Gratz, Daniel A. Jiménez   +2 more
openaire   +2 more sources