Results 81 to 90 of about 545,959 (267)

Determining the adjusting bias in reactor pressure vessel embrittlement trend curve using Bayesian multilevel modelling

Nuclear Engineering and Technology, 2023
A sophisticated Bayesian multilevel model for estimating group bias was developed to improve the utility of the ASTM E900-15 embrittlement trend curve (ETC) to assess the conditions of nuclear power plants (NPPs).
Gyeong-Geun Lee, Bong-Sang Lee, Min-Chul Kim, Jong-Min Kim   +3 more
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Multi-level Monte Carlo computation of the hadronic vacuum polarization contribution to (gμ − 2)

Physics Letters B, 2021
The hadronic contribution to the muon anomalous magnetic moment aμ=(gμ−2)/2 has to be determined at the per-mille level for the Standard Model prediction to match the expected final uncertainty from the ongoing E989 experiment.
Mattia Dalla Brida, Leonardo Giusti, Tim Harris, Michele Pepe   +3 more
doaj   +1 more source

Molecular Dynamics of pancake vortices with realistic interactions: Observing the vortex lattice melting transition

, 2005
In this paper we describe a version of London Langevin molecular dynamics simulations that allows for investigations of the vortex lattice melting transition in the highly anisotropic high-temperature superconductor material Bi$_2$Sr$_2$CaCu$_2$O$_{8 ...
A. E. Koshelev, I. S. Gradshteyn, M. Tinkham, S. Doniach, W. E. Lawrence, Yadin Y. Goldschmidt   +5 more
core   +1 more source

Interpretable Machine Learning for Solvent‐Dependent Carrier Mobility in Solution‐Processed Organic Thin Films

Advanced Intelligent Discovery, EarlyView.
This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley   +1 more source

The Effects of Misspecifying the Random Part of Multilevel Models

Methodology, 2020
This paper examined the amount bias in standard errors for fixed effects when the random part of a multilevel model is misspecified. Study 1 examined the effects of misspecification for a model with one Level 1 predictor.
David M. LaHuis, Daniel R. Jenkins, Michael J. Hartman, Shotaro Hakoyama, Patrick C. Clark   +4 more
doaj   +1 more source

Using Propensity Score Weighting With Clustered Data When the Treatment Is Applied at the Level of the Cluster and Outcomes Are Assessed at the Level of the Individual: The Observational Analog of Cluster Randomization Trials. [PDF]

Stat Med
ABSTRACT Propensity score methods allow researchers to mimic some (but not all) of the characteristics of a randomized controlled trial (RCT). Propensity score methods are usually applied to unstructured data, which allows one to mimic an RCT in which the individual is the unit of randomization.
Austin PC.
europepmc   +2 more sources

Multilevel higher-order quasi-Monte Carlo Bayesian estimation [PDF]

Mathematical Models and Methods in Applied Sciences, 2017
We propose and analyze deterministic multilevel (ML) approximations for Bayesian inversion of operator equations with uncertain distributed parameters, subject to additive Gaussian measurement data. The algorithms use a ML approach based on deterministic, higher-order quasi-Monte Carlo (HoQMC) quadrature for approximating the high-dimensional ...
Dick, J, Gantner, RN, Le Gia, QT, Schwab, C   +3 more
openaire   +4 more sources

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study.

Austrian Journal of Statistics, 2022
The multilevel and poststratification approach is commonly used to draw valid inference from (non-probabilistic) surveys. This Bayesian approach includes varying regression coefficients for which prior distributions of their variance parameter must be ...
Christian Bruch, Barbara Felderer
doaj   +1 more source