Yu Sun¹, Yi Ding^2,*, Junyi Jiang³, Vincent G. Duffy⁴

Computer Systems Science and Engineering, Vol.41, No.2, pp. 781-794, 2022, DOI:10.32604/csse.2022.016387

Abstract Mental workload is considered to be strongly linked to human performance, and the ability to measure it accurately is key for balancing human health and work. In this study, brain signals were elicited by mental arithmetic tasks of varying difficulty to stimulate different levels of mental workload. In addition, a finite impulse response (FIR) filter, independent component analysis (ICA), and multiple artifact rejection algorithms (MARAs) were used to filter event-related potentials (ERPs). Then, the data consisting of ERPs, subjective ratings of mental workload, and task performance, were analyzed through the use of variance and Spearman’s correlation during a simulated computer… More >

Mohammad Aldossary^*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3531-3562, 2021, DOI:10.32604/cmc.2021.017477

Abstract With the striking rise in penetration of Cloud Computing, energy consumption is considered as one of the key cost factors that need to be managed within cloud providers’ infrastructures. Subsequently, recent approaches and strategies based on reactive and proactive methods have been developed for managing cloud computing resources, where the energy consumption and the operational costs are minimized. However, to make better cost decisions in these strategies, the performance and energy awareness should be supported at both Physical Machine (PM) and Virtual Machine (VM) levels. Therefore, in this paper, a novel hybrid approach is proposed, which jointly considered the prediction… More >

Mohammad Aldossary^*

Computer Systems Science and Engineering, Vol.36, No.2, pp. 353-368, 2021, DOI:10.32604/csse.2021.014974

Abstract With the expansion of cloud computing, optimizing the energy efficiency and cost of the cloud paradigm is considered significantly important, since it directly affects providers’ revenue and customers’ payment. Thus, providing prediction information of the cloud services can be very beneficial for the service providers, as they need to carefully predict their business growths and efficiently manage their resources. To optimize the use of cloud services, predictive mechanisms can be applied to improve resource utilization and reduce energy-related costs. However, such mechanisms need to be provided with energy awareness not only at the level of the Physical Machine (PM) but… More >

Tengfei Yang^1,2, Xiaojun Shi³, Yangyang Li^1,*, Binbin Huang⁴, Haiyong Xie^1,5, Yanting Shen⁴

Journal on Big Data, Vol.2, No.3, pp. 105-115, 2020, DOI:10.32604/jbd.2020.010958

Abstract Mobile Edge Computing (MEC) has become the most possible network architecture to realize the vision of interconnection of all things. By offloading compute-intensive or latency-sensitive applications to nearby small cell base stations (sBSs), the execution latency and device power consumption can be reduced on resource-constrained mobile devices. However, computation delay of Mobile Edge Network (MEN) tasks are neglected while the unloading decision-making is studied in depth. In this paper, we propose a workload allocation scheme which combines the task allocation optimization of mobile edge network with the actual user behavior activities to predict the task allocation of single user. We… More >

Hossein Molaeifar¹, Farahnaz Khajehnasiri², Kiana Nikeghbal³, Zahra Zamanian^1,*

Sound & Vibration, Vol.54, No.3, pp. 139-148, 2020, DOI:10.32604/sv.2020.08810

Abstract Exposure to sound, heat, and increased physical workload can change physiological parameters. This study was conducted to evaluate the effect of concomitant exposure to sound, heat, and physical workload changes on physiological parameters in controlled laboratory conditions. This experimental crosssectional study was conducted in 35 male university students with a mean age of 25.75 years and a mean BMI of 22.69 kg/m² . Systolic and diastolic blood pressure and heart rate were measured after 15 min rest in the laboratory, 5 and 10 min after starting the experiment, and then after 20 min in controlled laboratory conditions in five combination… More >

Darcy N. Marckini¹, Bennett P. Samuel¹, Jessica L. Parker², Stephen C. Cook^1,3

Congenital Heart Disease, Vol.14, No.3, pp. 356-361, 2019, DOI:10.1111/chd.12745

Abstract Background: Physician burnout has many undesirable consequences, including nega‐ tive impact on patient care delivery and physician career satisfaction. Electronic health records (EHRs) may exacerbate burnout by increasing physician workload.
Objective: To determine burnout in adult congenital heart disease (ACHD) specialists by assessing stress associated with EHRs.
Design: Electronic survey study of ACHD providers.
Setting: Canada and United States.
Participants: Three hundred eighty‐three ACHD specialists listed on the Adult Congenital Heart Association directory between February and April 2017.
Outcome Measures: Burnout was measured using the Maslach Burnout Inventory (MBI) to understand factors contributing to work life and EHR satisfaction. Chi‐… More >