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Agent-based simulations have been widely applied in many disciplines, by scientists and engineers alike. Scientists use agent-based simulations to tackle global problems, including alleviating poverty, reducing violence, and predicting the impact of pandem ...
Sensing weak magnetic fields is a topic of great importance in basic science and technology due to its wide range of applications. In this context, solid-state and nanoscale quantum sensors are poised to revolutionize the sensing platforms due to their ult ...
Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...
This paper details the approach of the team Kohrrelation in the 2021 Extreme Value Analysis data challenge, dealing with the prediction of wildfire counts and sizes over the contiguous US. Our approach uses ideas from extreme-value theory in a machine lear ...
Following the 3rd release of the "Emerging PV reports", the best achievements in the performance of emerging photovoltaic (e-PV) devices in diverse e-PV research subjects are summarized, as reported in peer-reviewed articles in academic journals since Augu ...
The digital revolution has significantly transformed our world over the past decades, driven by the scaling of transistor dimensions and the exponential increase in computation power. However, as the CMOS scaling era approaches its end, the semiconductor i ...
Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validat ...
The evolution of electronics has largely relied on downscaling to meet the continuous needs for faster and highly integrated devices(1). As the channel length is reduced, however, classic electronic devices face fundamental issues that hinder exploiting ma ...
ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...
We study the privatization of distributed learning and optimization strategies. We focus on differential privacy schemes and study their effect on performance. We show that the popular additive random perturbation scheme degrades performance because it is ...
