The rapid growth of large-scale AI and machine learning workloads in globally distributed data centers has brought with it unprecedented computing power and, with it, an ever-increasing carbon ...
Given that extreme weather disturbances frequently threaten the safe and stable operation of new power systems, the uncertainty of source–load forecasting has become a particular bottleneck affecting ...
1 School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA. 2 Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA. As cloud ...
In this article, we advocate environmental equity as a priority for the management of future globally deployed AI systems. Concretely, we explore the potential of harnessing AI workloads’ scheduling ...
Many companies are searching for tools to help them hire diverse, productive workforces. Even if diversity is not the main hiring goal, they may want to ensure they’re not overlooking talented ...
Aiming at the poor robustness and adaptability of traditional control methods for different situations, the deep deterministic policy gradient (DDPG) algorithm is improved by designing a hybrid ...
[1] Bini, Enrico, and Giorgio C. Buttazzo. "Measuring the performance of schedulability tests." Real-Time Systems 30, no. 1 (2005): 129-154. [2] Davis, Robert I., and Alan Burns. "Improved priority ...
This paper provides a comprehensive review of Appointment Scheduling (AS) in healthcare service while we propose appointment scheduling problems and various applications and solution approaches in ...
1 Department of Industrial and Production Engineering, Basaveshwar Engineering College, Bagalkot, India. 2 Basaveshwar Engineering College, Bagalkot, India. 3 Gogte Institute of Technology, Belagavi, ...
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