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Learning to detect entity mentions without using syntactic information can be useful for integration and joint optimization with other tasks. However, it is common to have partially annotated data for this problem. Here, we investigate two approaches to de ...
PurposeThere is increasing interest in using fate and exposure models to spatially differentiate the impacts of chemical emissions. This work aims at exploring the operationalization in life cycle assessment (LCA) of spatially differentiated models for tox ...
The paper presents the implementation details and the experimental validation of a linear state estimator based on synchrophasor measurements in a real subtransmission network. The data are provided by 15 phasor measurement units (PMUs) installed in the 12 ...
We present constraints on local primordial non-Gaussianity (PNG), parametrized through f(NL)(loc), using the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 14 quasar sample. We measure and analyze the anisotropic ...
In the present article, we detail the method used to experimentally determine the power of the CROCUS zero-power reactor, and to subsequently calibrate its ex-core monitor fission chambers. Knowledge of the reactor power is a mandatory quantity for a safe ...
In failure-time settings, a competing event is any event that makes it impossible for the event of interest to occur. For example, cardiovascular disease death is a competing event for prostate cancer death because an individual cannot die of prostate canc ...
Travel time distributions (TTDs) are concise descriptions of transport processes in catchments based on water ages, and they are particularly efficient as lumped hydrological models to simulate tracers in outflows. Past studies have approximated catchment ...
Random binning features, introduced in the seminal paper of Rahimi and Recht '07, are an efficient method for approximating a kernel matrix using locality sensitive hashing. Random binning features provide a very simple and efficient way to approximate the ...
Diffusion adaptation is a powerful strategy for distributed estimation and learning over networks. Motivated by the concept of combining adaptive filters, this work proposes a combination framework that aggregates the operation of multiple diffusion strate ...
Purpose Regionalized life cycle impact assessment (LCIA) has rapidly developed in the past decade, though its widespread application, robustness, and validity still face multiple challenges. Under the umbrella of UNEP/SETAC Life Cycle Initiative, a dedicat ...