Results 131 to 140 of about 51,554 (281)

Adjusted predictions for generalized estimating equations

open access: yesBiometrics
ABSTRACT Generalized estimating equations (GEEs) are a popular statistical method for longitudinal data analysis, requiring specification of the first 2 marginal moments of the response along with a working correlation matrix to capture temporal correlations within a cluster.
Francis K C Hui   +2 more
openaire   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

open access: yesAdvanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt   +8 more
wiley   +1 more source

Trace Nickel Activated Biphasic Core‐CuOii/Shell‐CuOi Secondary Microspheres Enable Room Temperature Parts‐Per‐Trillion‐Level NO2 Detection

open access: yesAdvanced Engineering Materials, EarlyView.
An idea of designing novel sensors is proposed by creating appropriate Schottky barriers and vacancies between isomorphous Core‐CuOii/ Shell‐CuOi secondary microspheres and enhancing catalytic and spill‐over effects, and electronegativity via spontaneous biphasic separation, self‐assembly, and trace‐Ni‐doping.
Bala Ismail Adamu   +8 more
wiley   +1 more source

Probit Model on Multivariate Binary Response Using Simulated Maximum Likelihood Estimator

open access: yesJurnal Ilmu Dasar, 2010
In this paper, we discuss probit model on multivariate binary response. We assume that each of n individuals is observed in T responses. Yit is tth response on ith individual/subject and each response is binary.
Jaka Nugraha   +2 more
doaj  

Transfer Learning with General Estimating Equations

open access: yes
We consider statistical inference for parameters defined by general estimating equations under the covariate shift transfer learning. Different from the commonly used density ratio weighting approach, we undertake a set of formulations to make the statistical inference semiparametric efficient with simple inference.
Yan, Han, Chen, Song Xi
openaire   +2 more sources

Synchrotron Radiation for Quantum Technology

open access: yesAdvanced Functional Materials, EarlyView.
Materials and interfaces underpin quantum technologies, with synchrotron and FEL methods key to understanding and optimizing them. Advances span superconducting and semiconducting qubits, 2D materials, and topological systems, where strain, defects, and interfaces govern performance.
Oliver Rader   +10 more
wiley   +1 more source

Copper Doping Enhances the Activity and Selectivity of Atomically Precise Ag44 Nanoclusters for Photocatalytic CO2 Reduction

open access: yesAdvanced Functional Materials, EarlyView.
By a simple anti‐Galvanic reaction, up to six copper atoms could be preferably doped into the Ag2(SR)5 staple motifs and Ag20 dodecahedral shell of an atomically precise Ag44(SR)30 nanocluster. When anatase TiO2 is used as substrate, the (AgCu)44/TiO2 photocatalyst exhibited much improved activity in photocatalytic CO2 reduction compared to Ag44/TiO2 ...
Ye Liu   +5 more
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

open access: yesAdvanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone   +11 more
wiley   +1 more source

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