Results 41 to 50 of about 22,159 (266)
Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
This paper presents a nonparametric bootstrap multihop localization algorithm for large-scale wireless sensor networks (WSNs) in complex environments. Unlike most of the existing schemes, this work is based on the consideration that it is not feasible to
Yongji Ren +4 more
doaj +1 more source
The present study shows that Nrf2 directly binds to the Gm26550 promoter, thereby activating Gm26550 transcription and increasing its expression. Mechanistically, Gm26550 promotes IGF1 expression by functionally antagonizing miR‐26a‐5p‐mediated repression and sequestering the RBP KHSRP, thereby enhancing hippocampal neuronal synaptic plasticity and ...
Hongfang Wang +12 more
wiley +1 more source
Estimation and Simultaneous Confidence Bands for Fixed-Effects Panel Data Partially Linear Models
In this paper, we study the estimation and simultaneous confidence band (SCB) problems for fixed-effects panel data partially linear models. We remove the fixed effects and then obtain estimators for the parametric and nonparametric components, which do ...
Suigen Yang, Xiujuan Yang, Xuefei Wang
doaj +1 more source
A Non-parametric Bootstrap Method for Kinetic Monte Carlo Variance Reduction [PDF]
A new variance reduction technique for Monte Carlo transport methods is investigated. This approach is based on non-parametric bootstrapping, a statistical inference and resampling method which is used to generate simulated samples of Monte Carlo scores ...
Skretteberg Martin +2 more
doaj +1 more source
Nonparametric inference via bootstrapping the debiased estimator
In this paper, we propose to construct confidence bands by bootstrapping the debiased kernel density estimator (for density estimation) and the debiased local polynomial regression estimator (for regression analysis). The idea of using a debiased estimator was recently employed by Calonico et al.
Cheng, Gang, Chen, Yen-Chi
openaire +3 more sources
Do Universal Free School Meals Improve the Dietary Quality of Food‐At‐Home Purchases?
ABSTRACT Since 2014, the number of schools offering universal free meals to all enrolled children without requiring annual meal applications has increased meaningfully. Using USDA's Purchase to Plate Crosswalk, a difference‐in‐differences framework, and a nationwide consumer panel, the effect of universal‐free‐meal exposure on the diet quality of food ...
Xueying Ma +2 more
wiley +1 more source
Several procedures have been proposed for testing goodness-of-fit to the error distribution in nonparametric regression models. The null distribution of the associated test statistics is usually approximated by means of a parametric bootstrap which ...
G.I. Rivas-Martínez +1 more
doaj +1 more source
A computational approach to nonparametric regression: bootstrapping CMARS method [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ceyda Yazici +2 more
openaire +2 more sources
ABSTRACT This paper examines racial differences in farm succession planning using survey data from Tennessee farmers. While observed differences between White and Black farmers are small, decomposition and counterfactual analyses show that structural characteristics, particularly farm size, would predict higher succession planning among White farmers ...
Abdelaziz Lawani +2 more
wiley +1 more source

