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The ever-increasing penetration of Distributed Generators (DGs) in distribution networks suggests to enable their potentials in better fulfilling the restoration objective. The objective of the restoration problem is to resupply the maximum energy of loads ...
In developed countries, the management of existing civil infrastructure is challenging due to evolving functional requirements, aging and climate change. Due to conservative approaches in construction design and practice, infrastructure often has hidden re ...
The modeling of walking behavior and design of walk-friendly urban pathways have been of interest to many researchers over the past decades. One of the major issues in pedestrian modeling is path planning decision-making in a dynamic walking environment wi ...
Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique decision ...
SHiP is a proposed high-intensity beam dump experiment set to operate at the CERN SPS. It is expected to have an unprecedented sensitivity to a variety of models containing feebly interacting particles, such as Heavy Neutral Leptons (HNLs). Two HNLs or mor ...
Neural interfaces capable of multi-site electrical recording, on-site signal classification, and closed-loop therapy are critical for the diagnosis and treatment of neurological disorders. However, deploying machine learning algorithms on low-power neural ...
Fatigue safety verification of existing bridges that uses ‘‘re-calculation’’ based on codes, usually results in insufficient fatigue safety, triggering invasive interventions. Instead of “re-calculation”, Structural Health Monitoring (SHM) should be used f ...
Hierarchical architectures stacking primary, secondary, and tertiary layers are widely employed for the operation and control of islanded dc microgrids (dcmGs) composed of distribution generation units (DGUs), loads, and power lines. However, a comprehensi ...
%0 Conference Paper %T Bayesian Differential Privacy for Machine Learning %A Aleksei Triastcyn %A Boi Faltings %B Proceedings of the 37th International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2020 %E Hal Daumé III %E A ...
Little is known about the biological functions which are exerted by hormone receptors in physiological conditions. Here, we made use of the Mouse INtraDuctal (MIND) model, an innovative patient-derived xenograft (PDX) model, to characterize global gene exp ...