Results 61 to 70 of about 28,524 (229)
ABSTRACT Diagnosing high‐impedance ground faults (HIGFs) in distribution networks is extremely challenging because high transition resistance significantly reduces electrical signal strength and unpredictable initial fault phase angles coupled with asymmetric voltage disturbances often lead to misclassification.
Zhengyang Li +5 more
wiley +1 more source
SUBSPACE IDENTIFICATION - REDUCING UNCERTAINTY ON THE STOCHASTIC PART
Abstract Subspace identification algorithms are user friendly, numerical fast and stable and they provide a good consistent estimate of the deterministic part of a system. The weak point is the stochastic part. The uncertainty on this part is discussed below and methods to reduce it is derived.
openaire +4 more sources
A new indirect strategy is proposed to estimate the bridge modal parameters from the dynamic responses of two vehicles using stochastic subspace identification technique.
Jiantao Li +3 more
semanticscholar +1 more source
A popular method to conduct structural health monitoring is the spatio-temporal study of vibration signatures, where vibration properties are extracted from collected vibration responses.
A. Cancelli +4 more
semanticscholar +1 more source
To Grandmother's House We Go: Informal Childcare and Female Labor Mobility
ABSTRACT We document how childcare costs and the location of extended family influence the labor supply and mobility of US women. Women return to their home locations immediately before fertility events, suggesting that informal childcare needs may motivate home migration. Women who live near their parents have lower child earnings penalties.
Garrett Anstreicher, Joanna Venator
wiley +1 more source
On Metric Choice in Dimension Reduction for Fréchet Regression
Summary Fréchet regression is becoming a mainstay in modern data analysis for analysing non‐traditional data types belonging to general metric spaces. This novel regression method is especially useful in the analysis of complex health data such as continuous monitoring and imaging data.
Abdul‐Nasah Soale +3 more
wiley +1 more source
Monitoring panels of sparse functional data
Panels of random functions are common in applications of functional data analysis. They often occur when sequences of functions are observed at a number of different locations. We propose a methodology to monitor for structural breaks in such panels and to identify the changing components with statistical certainty.
Tim Kutta +2 more
wiley +1 more source
A Note on Local Polynomial Regression for Time Series in Banach Spaces
ABSTRACT This work extends local polynomial regression to Banach space‐valued time series for estimating smoothly varying means and their derivatives in non‐stationary data. The asymptotic properties of both the standard and bias‐reduced Jackknife estimators are analyzed under mild moment conditions, establishing their convergence rates.
Florian Heinrichs
wiley +1 more source
On the Existence of One‐Sided Representations for the Generalised Dynamic Factor Model
ABSTRACT We study the Generalised Dynamic Factor Model (GDFM) and show that the dynamic common component, that is, the common component of the GDFM, can be expressed using only current and past observations under mild assumptions. Specifically, we require (i) the dynamic common component to be purely non‐deterministic and (ii) the exclusion of ...
Philipp Gersing
wiley +1 more source
Operational modal analysis is a robust and practical approach to structural health monitoring which assumes white noise as input. Therefore, the accuracy of this method can be compromised when dealing with colored unknown excitations, in which, for ...
C. Rinaldi +4 more
doaj +1 more source

