25 papers · ranked by Valyu relevance
Frédéric Boucher, Julie Dextras-Gauthier, Marie-Hélène Gilbert, Pierre-Sebastien Fournier + 1 more
Background Like many other countries, healthcare services in Canada face numerous organizational changes with the main objective of doing more with less. The approach taken within different healthcare networks has brought about a reform in healthcare facilities in Quebec, leading to several mergers and eliminating over…
Dehe Li, Yinhuan Hu, Sha Liu, Chuntao Lu + 4 more
Background Previous studies, often simply using either objective workload or mental workload as a measure of physician workload in various healthcare settings might have failed to comprehensively reflect the real workload among physicians. Despite this, there is little research that further explores a comprehensive…
Joshua Bhagat Smith, Julie A. Adams
Successful human-robot teaming will require robots to adapt autonomously to a human teammate’s internal state, where a critical element is the ability to estimate the human’s workload in unknown situations. Existing workload models use machine learning to model the relationship between physiological signals and…
Sukhpal Singh, Inderveer Chana
— The Dynamic Scalability of resources, a problem in Infrastructure as a Service (IaaS) has been the hotspot for research and industry communities. The heterogeneous and dynamic nature of the Cloud workloads depends on the Quality of Service (QoS) allocation of appropriate workloads to appropriate resources. A workload…
Johannes Beller, Julia Graßhoff, Batoul Safieddine, Jelena Epping + 1 more
Background The adverse effects of perceived excessive workload (work overload), as one major source of work stress, on health and work performance are well-documented; however, studies that examine how work overload has changed over time are lacking. This study aims to examine the time trends in work overload across…
Quadri Adewale, George Panoutsos
Previous studies have shown that electroencephalogram (EEG) can be used in estimating mental workload. However, developing fast and reliable models for cross-task, cross-subject and cross-session classifications of workload remains a challenge. In this study, a wireless Emotiv EPOC headset was used to evaluate workload…
Claudine Mélan, Nadine Cascino
The present contribution presents two field studies combining tools and methods from cognitive psychology and from occupational psychology in order to perform a thorough investigation of workload in employees. Cognitive load theory proposes to distinguish different load categories of working memory, in a context of…
Cédric St-Onge, Souhila Benmakrelouf, Nadjia Kara, Hanine Tout + 2 more
'Claes Edstrom' 'Rafi Rabipour'] Workload models are typically built based on user and application behavior in a system, limiting them to specific domains. Undoubtedly, such a practice creates a dilemma in a cloud computing (cloud) environment, where a wide range of heterogeneous applications are running and many users…
Juan Liang, Wenxin Zhou, Bibo Xu, Hai Jiang
Introduction It is unclear what level of workload is best for workplace well-being, in part because researchers have only tested linear relationships. We tested an inverted U-shaped model in which workplace well-being is optimal at a moderate level of workload. The mediation effect of autonomous motivation were also…
Ayca Aygun, Thuan Nguyen, Matthias Scheutz
Robust estimation of systemic human cognitive states is critical for many applications, from simply detecting inefficiencies in human task performance to adapting the behaviors of artificial agents to improve team performance in mixed-initiative human-machine teams. Here we use comprehensive analyses of a multi-modal…
Roozbeh Aghili, Qiaolin Qin, Heng Li, Foutse Khomh
Systematic Literature Review and Characterization Authors: ['Roozbeh Aghili' 'Qiaolin Qin' 'Heng Li' 'Foutse Khomh'] Abstract—Web applications, accessible via web browsers over the Internet, facilitate complex functionalities without local software installation. In the context of web applications, a workload refers to…
Chansup Byun, Albert Reuther, Julie Mullen, Larry W. Anderson + 18 more
'William Arcand' 'Bill Bergeron' 'David Bestor' 'Alexander Bonn' 'Daniel Burrill' 'Vijay Gadepally' 'Michael E. Houle' 'Matthew Hubbell' 'Hayden Jananthan' 'Michael T. Jones' 'Piotr Łuszczek' 'Peter Michaleas' 'Lauren Milechin' 'Guillermo Morales' 'Andrew Prout' 'Antonio Rosa' 'Charles Yee' 'Jeremy Kepner']…
Mahdieh Nejati Javaremi, Di Wu, Brenna Argall
Shared human-robot control for assistive machines can improve the independence of individuals with motor impairments. Monitoring elevated levels of workload can enable the assistive autonomy to adjust the control-sharing in an assist-as-needed way, to achieve a balance between user fatigue, stress and independent…
Yongqi Han, Qingfeng Du, Jincheng Xu, Shengjie Zhao + 4 more
'Cao Li' 'Kanglin Yin' 'Dan Pei'] Artificial intelligence for IT Operations (AIOps) plays a critical role in operating and managing cloud-native systems and microservice-based applications but is limited by the lack of high-quality datasets with diverse scenarios. Realistic workloads are the premise and basis of…
Alka Rachel John, Avinash K Singh, Tien-Thong Nguyen Do, Ami Eidels + 12 more
The surge in air traffic increases the workload experienced by air traffic controllers (ATC) while they organise traffic-flow and prevent conflicts between aircraft. Even though several factors influence the complexity of ATC tasks, keeping track of the aircraft and preventing collision are the most crucial. We have…
Mohammad Arif Hossain, Derssie Mebratu, Niranjan Hasabnis, Jun Jin + 2 more
'Gaurav Chaudhary' 'Noah Shen'] Abstract—Workloads in modern cloud data centers are becoming increasingly complex. The number of workloads running in cloud data centers has been growing exponentially for the last few years, and cloud service providers (CSP) have been supporting on-demand services in real-time.…
Anjaly Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri + 3 more
'Timothy Zhu' 'Chetan Bansal'] Cloud providers introduce features (e.g., Spot VMs, Harvest VMs, and Burstable VMs) and optimizations (e.g., oversubscription, auto-scaling, power harvesting, and overclocking) to improve efficiency and reliability. To effectively utilize these features, it's crucial to understand the…
Feiyi Chen, Zhen Qin, Hailiang Zhao, MengChu Zhou + 1 more
—Cloud providers can greatly benefit from accurate workload prediction. However, the workload of cloud servers is highly variable, with occasional heavy workload bursts. This makes workload prediction challenging. There are mainly two categories of workload prediction methods: statistical methods and…
Xiaoguang Liu, Lu Shi, Cong Ye, Yangyang Li + 1 more
In the actual operation task, the workload of the oceanaut is mainly mental workload. For the oceanaut, too high or too low mental workload will significantly reduce work efficiency and even lead to major safety accidents. Classification of mental workload of the oceanaut in operational task research is one of the key…
Ayca Aygun, Thuan Nguyen, Matthias Scheutz
Robust estimation of systemic human cognitive states is critical for a variety of applications, from simply detecting inefficiencies in task assignments, to the adaptation of artificial agents’ behaviors to improve team performance in mixed-initiative human-machine teams. This study showed that human eye gaze, in…
Shaoyuan Huang, Zheng Wang, Heng Zhang, Xiaofei Wang + 2 more
'Wenyu Wang'] Workload prediction in multi-tenant edge cloud platforms (MT-ECP) is vital for efficient application deployment and resource provisioning. However, the heterogeneous application patterns, variable infrastructure performance, and frequent deployments in MT-ECP pose significant challenges for accurate and…
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This work focuses on a novel human-centered digital assistant combining Mixed Reality (MR), Computer Vision and Machine Learning regression to guide professionals and students on how to operate and correctly parameterize battery manufacturing machinery. Our Concept article aim is to provide a proof of concept of our…
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Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
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Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
Mahnoor Zulfiqar, Michael R. Crusoe, Birgitta König-Ries, Christoph Steinbeck + 2 more
Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for…